Metadata-Version: 2.4
Name: agent-lexicon
Version: 0.2.0
Summary: A lightweight terminology memory layer for AI agents.
Project-URL: Homepage, https://github.com/SkeinRank/agent-lexicon
Project-URL: Repository, https://github.com/SkeinRank/agent-lexicon
Project-URL: Issues, https://github.com/SkeinRank/agent-lexicon/issues
Author: SkeinRank
License:                               Apache License
                                Version 2.0, January 2004
                             http://www.apache.org/licenses/
        
        TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
        
        1. Definitions.
        
           "License" shall mean the terms and conditions for use, reproduction,
           and distribution as defined by Sections 1 through 9 of this document.
        
           "Licensor" shall mean the copyright owner or entity authorized by
           the copyright owner that is granting the License.
        
           "Legal Entity" shall mean the union of the acting entity and all
           other entities that control, are controlled by, or are under common
           control with that entity. For the purposes of this definition,
           "control" means (i) the power, direct or indirect, to cause the
           direction or management of such entity, whether by contract or
           otherwise, or (ii) ownership of fifty percent (50%) or more of the
           outstanding shares, or (iii) beneficial ownership of such entity.
        
           "You" (or "Your") shall mean an individual or Legal Entity
           exercising permissions granted by this License.
        
           "Source" form shall mean the preferred form for making modifications,
           including but not limited to software source code, documentation
           source, and configuration files.
        
           "Object" form shall mean any form resulting from mechanical
           transformation or translation of a Source form, including but
           not limited to compiled object code, generated documentation,
           and conversions to other media types.
        
           "Work" shall mean the work of authorship, whether in Source or
           Object form, made available under the License, as indicated by a
           copyright notice that is included in or attached to the work
           (an example is provided in the Appendix below).
        
           "Derivative Works" shall mean any work, whether in Source or Object
           form, that is based on (or derived from) the Work and for which the
           editorial revisions, annotations, elaborations, or other modifications
           represent, as a whole, an original work of authorship. For the purposes
           of this License, Derivative Works shall not include works that remain
           separable from, or merely link (or bind by name) to the interfaces of,
           the Work and Derivative Works thereof.
        
           "Contribution" shall mean any work of authorship, including
           the original version of the Work and any modifications or additions
           to that Work or Derivative Works thereof, that is intentionally
           submitted to Licensor for inclusion in the Work by the copyright owner
           or by an individual or Legal Entity authorized to submit on behalf of
           the copyright owner. For the purposes of this definition, "submitted"
           means any form of electronic, verbal, or written communication sent
           to the Licensor or its representatives, including but not limited to
           communication on electronic mailing lists, source code control systems,
           and issue tracking systems that are managed by, or on behalf of, the
           Licensor for the purpose of discussing and improving the Work, but
           excluding communication that is conspicuously marked or otherwise
           designated in writing by the copyright owner as "Not a Contribution."
        
           "Contributor" shall mean Licensor and any individual or Legal Entity
           on behalf of whom a Contribution has been received by Licensor and
           subsequently incorporated within the Work.
        
        2. Grant of Copyright License. Subject to the terms and conditions of
           this License, each Contributor hereby grants to You a perpetual,
           worldwide, non-exclusive, no-charge, royalty-free, irrevocable
           copyright license to reproduce, prepare Derivative Works of,
           publicly display, publicly perform, sublicense, and distribute the
           Work and such Derivative Works in Source or Object form.
        
        3. Grant of Patent License. Subject to the terms and conditions of
           this License, each Contributor hereby grants to You a perpetual,
           worldwide, non-exclusive, no-charge, royalty-free, irrevocable
           (except as stated in this section) patent license to make, have made,
           use, offer to sell, sell, import, and otherwise transfer the Work,
           where such license applies only to those patent claims licensable
           by such Contributor that are necessarily infringed by their
           Contribution(s) alone or by combination of their Contribution(s)
           with the Work to which such Contribution(s) was submitted. If You
           institute patent litigation against any entity (including a
           cross-claim or counterclaim in a lawsuit) alleging that the Work
           or a Contribution incorporated within the Work constitutes direct
           or contributory patent infringement, then any patent licenses
           granted to You under this License for that Work shall terminate
           as of the date such litigation is filed.
        
        4. Redistribution. You may reproduce and distribute copies of the
           Work or Derivative Works thereof in any medium, with or without
           modifications, and in Source or Object form, provided that You
           meet the following conditions:
        
           (a) You must give any other recipients of the Work or
               Derivative Works a copy of this License; and
        
           (b) You must cause any modified files to carry prominent notices
               stating that You changed the files; and
        
           (c) You must retain, in the Source form of any Derivative Works
               that You distribute, all copyright, patent, trademark, and
               attribution notices from the Source form of the Work,
               excluding those notices that do not pertain to any part of
               the Derivative Works; and
        
           (d) If the Work includes a "NOTICE" text file as part of its
               distribution, then any Derivative Works that You distribute must
               include a readable copy of the attribution notices contained
               within such NOTICE file, excluding those notices that do not
               pertain to any part of the Derivative Works, in at least one
               of the following places: within a NOTICE text file distributed
               as part of the Derivative Works; within the Source form or
               documentation, if provided along with the Derivative Works; or,
               within a display generated by the Derivative Works, if and
               wherever such third-party notices normally appear. The contents
               of the NOTICE file are for informational purposes only and
               do not modify the License. You may add Your own attribution
               notices within Derivative Works that You distribute, alongside
               or as an addendum to the NOTICE text from the Work, provided
               that such additional attribution notices cannot be construed
               as modifying the License.
        
           You may add Your own copyright statement to Your modifications and
           may provide additional or different license terms and conditions
           for use, reproduction, or distribution of Your modifications, or
           for any such Derivative Works as a whole, provided Your use,
           reproduction, and distribution of the Work otherwise complies with
           the conditions stated in this License.
        
        5. Submission of Contributions. Unless You explicitly state otherwise,
           any Contribution intentionally submitted for inclusion in the Work
           by You to the Licensor shall be under the terms and conditions of
           this License, without any additional terms or conditions.
           Notwithstanding the above, nothing herein shall supersede or modify
           the terms of any separate license agreement you may have executed
           with Licensor regarding such Contributions.
        
        6. Trademarks. This License does not grant permission to use the trade
           names, trademarks, service marks, or product names of the Licensor,
           except as required for reasonable and customary use in describing the
           origin of the Work and reproducing the content of the NOTICE file.
        
        7. Disclaimer of Warranty. Unless required by applicable law or
           agreed to in writing, Licensor provides the Work (and each
           Contributor provides its Contributions) on an "AS IS" BASIS,
           WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
           implied, including, without limitation, any warranties or conditions
           of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
           PARTICULAR PURPOSE. You are solely responsible for determining the
           appropriateness of using or redistributing the Work and assume any
           risks associated with Your exercise of permissions under this License.
        
        8. Limitation of Liability. In no event and under no legal theory,
           whether in tort (including negligence), contract, or otherwise,
           unless required by applicable law (such as deliberate and grossly
           negligent acts) or agreed to in writing, shall any Contributor be
           liable to You for damages, including any direct, indirect, special,
           incidental, or consequential damages of any character arising as a
           result of this License or out of the use or inability to use the
           Work (including but not limited to damages for loss of goodwill,
           work stoppage, computer failure or malfunction, or any and all
           other commercial damages or losses), even if such Contributor
           has been advised of the possibility of such damages.
        
        9. Accepting Warranty or Additional Liability. While redistributing
           the Work or Derivative Works thereof, You may choose to offer,
           and charge a fee for, acceptance of support, warranty, indemnity,
           or other liability obligations and/or rights consistent with this
           License. However, in accepting such obligations, You may act only
           on Your own behalf and on Your sole responsibility, not on behalf
           of any other Contributor, and only if You agree to indemnify,
           defend, and hold each Contributor harmless for any liability
           incurred by, or claims asserted against, such Contributor by reason
           of your accepting any such warranty or additional liability.
        
        END OF TERMS AND CONDITIONS
        
        APPENDIX: How to apply the Apache License to your work.
        
           To apply the Apache License to your work, attach the following
           boilerplate notice, with the fields enclosed by brackets "[]"
           replaced with your own identifying information. (Don't include
           the brackets!)  The text should be enclosed in the appropriate
           comment syntax for the file format. We also recommend that a
           file or class name and description of purpose be included on the
           same "printed page" as the copyright notice for easier
           identification within third-party archives.
        
        Copyright [yyyy] [name of copyright owner]
        
        Licensed under the Apache License, Version 2.0 (the "License");
        you may not use this file except in compliance with the License.
        You may obtain a copy of the License at
        
            http://www.apache.org/licenses/LICENSE-2.0
        
        Unless required by applicable law or agreed to in writing, software
        distributed under the License is distributed on an "AS IS" BASIS,
        WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
        See the License for the specific language governing permissions and
        limitations under the License.
License-File: LICENSE
Keywords: ai-agents,governance,lexicon,rag,terminology,tool-use
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Typing :: Typed
Requires-Python: >=3.10
Description-Content-Type: text/markdown

# Agent Lexicon

Shared terminology memory for AI agents.

Agent Lexicon is a lightweight Python package for giving agents a small,
reviewable terminology layer before RAG, tool calls, and workflow automation.

## Install

```bash
pip install agent-lexicon
```

## Quick check

```bash
agent-lexicon --version
python -m agent_lexicon --version
agent-lexicon validate examples/customer_limits/lexicon.yaml
agent-lexicon match examples/customer_limits/lexicon.yaml "The customer cap and rate limit changed." --longest-only
agent-lexicon resolve examples/customer_limits/lexicon.yaml "increase the limit"
agent-lexicon guard examples/customer_limits/lexicon.yaml "increase the limit" --tool api.update_rate_limit
agent-lexicon validate-queries examples/customer_limits/queries.jsonl
agent-lexicon check examples/customer_limits/lexicon.yaml examples/customer_limits/queries.jsonl
agent-lexicon ingest README.md src examples/customer_limits/docs --root .
agent-lexicon discover-candidates examples/customer_limits/docs --root examples/customer_limits
agent-lexicon build-evidence examples/customer_limits/docs --root examples/customer_limits
```

## Core schema

The package includes dependency-free core models for terminology workflows:

- `Scope` — a project, team, domain, or workflow boundary where a term has a specific meaning.
- `Term` — a canonical domain term with aliases, scopes, tags, evidence, and metadata.
- `Alias` — a surface form that points to a canonical term.
- `EvidenceSpan` — a source-backed snippet with file path, line range, and evidence kind.
- `ProposalCandidate` — a reviewable terminology change suggested by local analysis or an agent.
- `Lexicon` — a validated terminology document containing scopes, terms, proposals, and metadata.

Example:

```python
from agent_lexicon import Alias, EvidenceSpan, ProposalCandidate, ProposalKind, Term

term = Term(
    id="billing.credit_limit",
    canonical="credit limit",
    aliases=(Alias(surface="customer cap", term_id="billing.credit_limit"),),
    scopes=("billing",),
)

evidence = EvidenceSpan(
    source_path="docs/billing.md",
    start_line=42,
    snippet="Customer cap is the credit limit for an account.",
)

proposal = ProposalCandidate(
    id="proposal.customer-cap.alias",
    kind=ProposalKind.ALIAS_CANDIDATE,
    surface="customer cap",
    candidate_term_id="billing.credit_limit",
    confidence=0.78,
    evidence=(evidence,),
)
```

## Lexicon documents

Agent Lexicon can load and validate JSON or YAML terminology documents. The
current document format is intentionally small and local-first:

```yaml
version: 1
scopes:
  - id: billing
    label: Billing
terms:
  - id: billing.credit_limit
    canonical: credit limit
    scopes: [billing]
    tools: [billing.update_credit_limit]
    aliases:
      - surface: customer cap
        scopes: [billing]
    evidence:
      - source_path: docs/billing.md
        start_line: 12
        snippet: Customer cap is the credit limit for an account.
        kind: positive
```

Validate a document from the command line:

```bash
agent-lexicon validate examples/customer_limits/lexicon.yaml
agent-lexicon match examples/customer_limits/lexicon.yaml "The customer cap and rate limit changed." --longest-only
agent-lexicon resolve examples/customer_limits/lexicon.yaml "increase the limit"
agent-lexicon guard examples/customer_limits/lexicon.yaml "increase the limit" --tool api.update_rate_limit
```

Load the same document from Python:

```python
from agent_lexicon import Lexicon, load_lexicon

lexicon = load_lexicon("examples/customer_limits/lexicon.yaml")
assert lexicon.get_term("billing.credit_limit") is not None

lexicon_again = Lexicon.from_file("examples/customer_limits/lexicon.json")
```

The loader validates duplicate ids, unknown scope references, alias collisions,
and proposal references before returning a `Lexicon` object.


## Surface matching

Agent Lexicon can scan text for canonical terms and aliases from a loaded
lexicon. The matcher is dependency-free and uses a trie with Aho-Corasick
failure links, so it can be used by runtime agents before retrieval, tool calls,
or local review workflows.

```python
from agent_lexicon import build_surface_matcher, load_lexicon

lexicon = load_lexicon("examples/customer_limits/lexicon.yaml")
matcher = build_surface_matcher(lexicon)

matches = matcher.match(
    "The customer cap and rate limit changed.",
    longest_only=True,
)

for match in matches:
    print(match.term_id, match.kind.value, match.matched_text)
```

Command line usage:

```bash
agent-lexicon match examples/customer_limits/lexicon.yaml "The customer cap and rate limit changed."
```

The matcher supports scope filtering, case-sensitive aliases, deprecated surface
filtering, and longest non-overlapping output for downstream resolver logic.


## Runtime resolution

The resolver turns surface matches into a deterministic runtime decision. It
prefers longer non-overlapping surfaces, preserves same-span ambiguity, and
returns one of three statuses: `resolved`, `ambiguous`, or `unknown`.

```python
from agent_lexicon import load_lexicon, resolve_text

lexicon = load_lexicon("examples/customer_limits/lexicon.yaml")

decision = resolve_text(lexicon, "increase the limit")
print(decision.status.value)  # ambiguous
print(decision.action.value)  # ask_clarification

billing_decision = resolve_text(
    lexicon,
    "increase the limit",
    scopes=("billing",),
)
print(billing_decision.primary_term_id)  # billing.credit_limit
```

Command line usage:

```bash
agent-lexicon resolve examples/customer_limits/lexicon.yaml "increase the limit"
agent-lexicon guard examples/customer_limits/lexicon.yaml "increase the limit" --tool api.update_rate_limit
agent-lexicon resolve examples/customer_limits/lexicon.yaml "increase the limit" --scope billing
```

This gives agents a local way to stop before unsafe assumptions: if the same
surface can mean multiple canonical terms, the recommended action is
`ask_clarification`.


## Tool-call safety

Agent Lexicon can check a requested tool call before the agent executes it. If
terminology is ambiguous, the guard asks for clarification instead of allowing a
risky tool call. If a term is resolved and declares allowed tools, the requested
tool must match that term's tool list.

```python
from agent_lexicon import guard_tool_call, load_lexicon

lexicon = load_lexicon("examples/customer_limits/lexicon.yaml")

decision = guard_tool_call(
    lexicon,
    "increase the limit",
    tool_name="api.update_rate_limit",
)

print(decision.status.value)  # needs_clarification
print(decision.action.value)  # ask_clarification
print(decision.is_allowed)    # False
```

Command line usage:

```bash
agent-lexicon guard examples/customer_limits/lexicon.yaml "increase the limit" --tool api.update_rate_limit
agent-lexicon guard examples/customer_limits/lexicon.yaml "increase the limit" --tool billing.update_credit_limit --scope billing
```

The `guard` command returns `0` for allowed or no-match decisions and `2` when
the tool call is blocked or needs clarification. This makes it usable in local
agent wrappers and future CI checks.



## Local ingest

Agent Lexicon can read local project files into deterministic text documents for
future scout, evidence, and review workflows. Directory scans use local-project
defaults: README files, `docs/`, `src/`, Markdown, JSON/YAML, TOML, and common
text/code files. Large files, binary files, virtual environments, build outputs,
and cache directories are skipped.

Command line usage:

```bash
agent-lexicon ingest README.md src examples/customer_limits/docs --root .
agent-lexicon discover-candidates examples/customer_limits/docs --root examples/customer_limits
agent-lexicon build-evidence examples/customer_limits/docs --root examples/customer_limits
agent-lexicon ingest examples/customer_limits/docs --root examples/customer_limits --jsonl
```

Python usage:

```python
from agent_lexicon import ingest_local_paths

report = ingest_local_paths(["README.md", "src", "examples/customer_limits/docs"], root=".")

for document in report.documents:
    print(document.relative_path, document.kind.value, document.line_count)
```

The ingest report exposes `document_count`, `total_lines`, `total_size_bytes`,
`documents`, and `skipped_paths`. Each document includes a stable SHA-256 hash,
relative path, source kind, line count, byte size, and text content.

## Candidate discovery

Agent Lexicon can run a deterministic local scout pass over ingested documents.
The scout discovers reviewable terminology candidates, assigns a score, reports
a jargon score, and applies background penalties so common project words do not
dominate the candidate list. This step is local-first and dependency-free.

Command line usage:

```bash
agent-lexicon discover-candidates examples/customer_limits/docs --root examples/customer_limits
agent-lexicon discover-candidates examples/customer_limits/docs --root examples/customer_limits --lexicon examples/customer_limits/lexicon.yaml --json
```

Python usage:

```python
from agent_lexicon import discover_scout_candidates, ingest_local_paths

ingest_report = ingest_local_paths(["examples/customer_limits/docs"], root="examples/customer_limits")
candidate_report = discover_scout_candidates(ingest_report.documents)

for candidate in candidate_report.candidates:
    print(candidate.surface, candidate.score, candidate.jargon_score, candidate.background_penalty)
```

Each candidate includes a surface, normalized surface, kind, score, jargon
score, background penalty, occurrence count, document count, source occurrences,
and a deterministic score breakdown. Existing lexicon surfaces can be filtered
out with `existing_surfaces_from_lexicon(...)` or the CLI `--lexicon` option.

## Evidence packs

Evidence packs turn discovered candidates into reviewable snippets with file
paths and line numbers. Positive snippets show exact candidate occurrences.
Negative snippets show partial token overlap without the exact surface, which
helps reviewers spot broad, overloaded, or weak terminology candidates.

Command line usage:

```bash
agent-lexicon build-evidence examples/customer_limits/docs --root examples/customer_limits
agent-lexicon build-evidence examples/customer_limits/docs --root examples/customer_limits --json
agent-lexicon build-evidence examples/customer_limits/docs --root examples/customer_limits --jsonl
```

Python usage:

```python
from agent_lexicon import build_evidence_packs, discover_scout_candidates, ingest_local_paths

ingest_report = ingest_local_paths(["examples/customer_limits/docs"], root="examples/customer_limits")
candidate_report = discover_scout_candidates(ingest_report.documents)
evidence_report = build_evidence_packs(ingest_report.documents, candidate_report.candidates)

for pack in evidence_report.packs:
    print(pack.surface, pack.positive_count, pack.negative_count)
```

Each pack includes the candidate surface, score, positive snippets, negative
snippets, line ranges, reasons, and source metadata. This is the local evidence
foundation for proposal review and future snapshot publishing.

## Behavior metrics

Agent Lexicon can run deterministic behavior checks against a local `queries.jsonl` dataset.
The report measures terminology resolution, ambiguity detection, canonicalization,
and unsafe tool-call prevention.

```bash
agent-lexicon check examples/customer_limits/lexicon.yaml examples/customer_limits/queries.jsonl
```

Example output:

```text
Behavior check: 38/38 checks passed across 5 queries
Overall accuracy: 100.0%
Ambiguity detection: 100.0%
Canonicalization: 100.0%
Wrong tool prevention: 100.0%
Tool status: 100.0%
Tool allowed: 100.0%
```

For automation and dashboards, the same report can be emitted as JSON:

```bash
agent-lexicon check examples/customer_limits/lexicon.yaml examples/customer_limits/queries.jsonl --json
```

## Development

Install the development environment with Poetry:

```bash
poetry install --with dev
```

Run the test suite:

```bash
poetry run pytest -q
```

The repository also includes Make targets for the same workflow:

```bash
make install
make test
make check
```

## Relationship to SkeinRank

Agent Lexicon is intended to be the lightweight runtime SDK that agents can call
locally. SkeinRank remains the enterprise control plane for terminology drift,
proposal review, governed snapshots, and search/RAG integration.

## License

Apache License 2.0.

## Eval query datasets

Agent Lexicon uses JSONL query datasets to describe expected runtime behavior.
Each row contains one user query, optional scopes, expected terminology
resolution, and optional tool-call safety expectations. Metrics are computed by
the evaluation runner, while this layer keeps the dataset format validated and
portable.

Example row:

```json
{"id":"ambiguous.limit","text":"increase the limit","expected_status":"ambiguous","expected_action":"ask_clarification","expected_term_ids":["billing.credit_limit","api.rate_limit"],"tool_calls":[{"tool_name":"api.update_rate_limit","expected_status":"needs_clarification","expected_action":"ask_clarification","expected_allowed":false}]}
```

Validate a dataset from the command line:

```bash
agent-lexicon validate-queries examples/customer_limits/queries.jsonl
agent-lexicon check examples/customer_limits/lexicon.yaml examples/customer_limits/queries.jsonl
agent-lexicon ingest README.md src examples/customer_limits/docs --root .
agent-lexicon discover-candidates examples/customer_limits/docs --root examples/customer_limits
agent-lexicon build-evidence examples/customer_limits/docs --root examples/customer_limits
```

Load the same dataset from Python:

```python
from agent_lexicon import load_eval_queries

queries = load_eval_queries("examples/customer_limits/queries.jsonl")
assert queries[0].expected_status.value == "ambiguous"
```

The loader validates duplicate ids, JSONL structure, expected resolver statuses,
expected resolver actions, tool guard statuses, tool guard actions, and primary
term references before returning typed query objects.

