Metadata-Version: 2.4
Name: paper-scoring-skills
Version: 0.2.0
Summary: Cross-agent Paper Scoring Skill and installer
Project-URL: Repository, https://github.com/maikeruSan/paper-scoring-skills
Author: Paper Scoring contributors
License: MIT License
        
        Copyright (c) 2026 Paper Scoring contributors
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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License-File: LICENSE
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.11
Requires-Dist: paper-scoring-digest<0.2.0,>=0.1.0
Requires-Dist: paper-scoring-mcp<0.2.0,>=0.1.0
Provides-Extra: all
Requires-Dist: paper-scoring-digest<0.2.0,>=0.1.0; extra == 'all'
Requires-Dist: paper-scoring-mcp[all]<0.2.0,>=0.1.0; extra == 'all'
Provides-Extra: ollama
Requires-Dist: paper-scoring-mcp[ollama]<0.2.0,>=0.1.0; extra == 'ollama'
Provides-Extra: openai
Requires-Dist: paper-scoring-mcp[openai]<0.2.0,>=0.1.0; extra == 'openai'
Provides-Extra: openalex
Requires-Dist: paper-scoring-mcp[openalex]<0.2.0,>=0.1.0; extra == 'openalex'
Provides-Extra: security
Requires-Dist: bandit<2,>=1.8; extra == 'security'
Requires-Dist: detect-secrets<2,>=1.5; extra == 'security'
Requires-Dist: pip-audit<3,>=2.9; extra == 'security'
Provides-Extra: test
Requires-Dist: build<2,>=1.3; extra == 'test'
Requires-Dist: coverage[toml]<8,>=7.10; extra == 'test'
Requires-Dist: mypy<2,>=1.17; extra == 'test'
Requires-Dist: packaging<27,>=25; extra == 'test'
Requires-Dist: pytest<10,>=9.0.3; extra == 'test'
Requires-Dist: pyyaml<7,>=6; extra == 'test'
Requires-Dist: ruff<1,>=0.12; extra == 'test'
Requires-Dist: twine<7,>=6.2; extra == 'test'
Description-Content-Type: text/markdown

# Paper Scoring Skills

One canonical Agent Skill for using the Paper Scoring MCP server from Codex,
Claude Code, OpenClaw, and Hermes. The installer copies files and never relies
on symlinks, so it works on Ubuntu and Windows.

## Install

```shell
pip install "paper-scoring-skills[openai]==0.2.0"
paper-scoring-skills install --client codex --scope user
```

Use the `ollama` or `all` extra instead when appropriate. Supported clients are
`codex`, `claude`, `openclaw`, and `hermes`. For a project installation, run
from the repository or OpenClaw workspace root:

```shell
paper-scoring-skills install --client claude --scope project
```

Hermes project installs use `.hermes/skills` and require an explicit trust
decision from inside the repository:

```shell
paper-scoring-skills install --client hermes --scope project
hermes skills trust
```

## Connect the MCP server

The Skill deliberately does not embed credentials or a fixed remote URL.
Register the installed local server over STDIO. The following examples show
runtime dotenv injection; replace the sample absolute path with the appropriate
POSIX or Windows path. Omit the final two server arguments when no dotenv file
is needed.

Codex:

```shell
codex mcp add paper-scoring -- paper-scoring-mcp --transport stdio --env-file /absolute/path/runtime.env
```

Claude Code:

```shell
claude mcp add --transport stdio --scope user paper-scoring -- paper-scoring-mcp --transport stdio --env-file /absolute/path/runtime.env
```

OpenClaw:

```shell
openclaw mcp add paper-scoring --command paper-scoring-mcp --arg=--transport --arg=stdio --arg=--env-file --arg=/absolute/path/runtime.env
openclaw mcp doctor paper-scoring --probe
```

For Hermes, add this entry under `mcp_servers` in `~/.hermes/config.yaml`, then
run `/reload-mcp`:

```yaml
paper_scoring:
  command: paper-scoring-mcp
  args: [--transport, stdio, --env-file, /absolute/path/runtime.env]
```

The installed Skill contains no credentials. Configure the MCP server through
its process environment or explicit `--env-file` option.

## Discuss a daily digest

Version 0.2 also installs `paper-scoring-digest`. In an OpenClaw Slack thread,
the Skill maps a reply such as `3, 7: compare the methods` to the exact stored
run and ranks. It reads retained PDFs for page-level discussion and does not
silently rescore the papers. PDFs expire after the digest service's configured
retention period; metadata, scores, and arXiv links remain available.
