Agent skill

Self Review Round Two

by pyathena-dev in pyathena-dev/PyAthena

Run the second PyAthena self-review after round one, auditing factual claims, caller compatibility, AWS operational effects, and evidence from a user's perspective before Ready.

MITAuto-check passedDatabases

Install Self Review Round Two

skills CLI
$ npx skills add pyathena-dev/PyAthena --skill self-review-round-two -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install pyathena-dev/PyAthena self-review-round-two --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/pyathena-dev/PyAthena.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/self-review-round-two .claude/skills/self-review-round-two && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
self-review-round-two
GitHub stars
493
Token cost
~820 tokens
SKILL.md length
389 words
Files
1
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

Run the second PyAthena self-review after round one, auditing factual claims, caller compatibility, AWS operational effects, and evidence from a user's perspective before Ready.

  • Databases work in your project
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Self Review Round Two is an agent skill from pyathena-dev/PyAthena. Run the second PyAthena self-review after round one, auditing factual claims, caller compatibility, AWS operational effects, and evidence from a user's perspective before Ready.

Its SKILL.md is about 820 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases. It works with Amazon Web Services, Python and SQLAlchemy. The repository describes itself as: PyAthena is a Python DB API 2.0 (PEP 249) client for Amazon Athena. The licence is MIT.

When your agent uses it

  • Databases work in your project

Example prompts

  • “/self-review-round-two”

What it can do on your machine

Read from SKILL.md and the folder at commit 971dd12. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Self Review Round Two loads about 820 tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 389 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~820

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from pyathena-dev/PyAthena at commit 971dd12, republished under its MIT licence (© pyathena-dev). 389 words, ~820 tokens.

Download SKILL.mdSave it as .claude/skills/self-review-round-two/SKILL.md (or your agent's skills folder).
name
self-review-round-two
description
Run the second PyAthena self-review after round one, auditing factual claims, caller compatibility, AWS operational effects, and evidence from a user's perspective before Ready.

Self-review of claims and operational behavior

Use the scope and evidence rules in development-workflow. Honor any explicit review-only restrictions on corpus, commands, and side effects. This round tests whether the change's explanation and guarantees hold for callers and operators. Rereading round one's implementation checklist does not complete this round.

Before inspecting implementation details, list actionable factual claims in the PR body, changed docstrings/comments, documentation, commit messages, and issue premises repeated by the change. For each claim, identify evidence that could disprove it and examine the relevant callers, dependency sources, or measurements. An issue report alone is not proof of its proposed cause.

PerspectivePyAthena questions
Existing callerDo defaults, positional/keyword arguments, return shapes, exceptions, optional dependencies, and supported Python/SQLAlchemy versions still work? Does a mutable or one-shot input behave differently across repeated calls?
AWS operatorHow do botocore and application retries compose? What bounds attempts and elapsed time? Is a quota diagnosis based on the actual API, region/account, and run, or merely on an error string? Does reducing requests preserve freshness and error visibility?
Adversarial callerCan another Inspector, schema, catalog, backend, concurrent request, or DDL operation break a stated cache or lifecycle guarantee? Check absence versus failure and stale versus fresh metadata where applicable.
Documentation readerDo the examples work with the documented dependencies and environment? Search related docs and examples for statements the change makes obsolete, including prose outside the diff.
Evidence reviewerDo tests exercise both success and failure with meaningful assertions? Separate local from CI, synchronous from asynchronous, and fake-provider counts from measured AWS traffic. Does the result belong to the published revision?
Show full SKILL.md (122 more words)Show less

Measure a performance or service claim when the authorized environment permits it, or narrow the claim to the evidence available. Document unmeasured limits explicitly; do not present a static source review as runtime validation. Do not add retries or weaken a test to hide an unexplained failure. For documentation-only changes, walk through the commands and decision paths; do not launch AWS tests just to complete a checklist.

Correct false claims in the PR description and affected prose, and validate any implementation repairs. Record claims checked, supporting evidence, corrections, and reasoned deferrals as round two. For small wording changes, this can be a short claim-and-link check, but it remains a distinct recorded pass. Proceed to independent-review only after both self-review rounds are complete.

© pyathena-dev, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/self-review-round-two of pyathena-dev/PyAthena.

Open the folder on GitHubat commit 971dd12

Compare with similar skills

Self Review Round Two next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Self Review Round Two compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Self Review Round Two this skillpyathena-dev/PyAthena493—~820Automated safety check: PassMIT
Mastering Python SkillSpillwaveSolutions/agent-brain119—~1.4kAutomated safety check: NotesMIT
AWS Dynamodbalinaqi/maggy707—~4.6kAutomated safety check: PassMIT
Using Relational Databasesancoleman/ai-design-components526—~2.5kAutomated safety check: PassMIT
AWS SDK Python Usageaws/agent-toolkit-for-aws2.8k1 repos~2.1kAutomated safety check: PassApache-2.0
Supabase Pythonalinaqi/maggy707—~4kAutomated safety check: NotesMIT

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More from pyathena-dev/PyAthena

  • Development Workflow

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    Deliver a PyAthena change through a dedicated worktree, Draft PR, two distinct self-reviews, independent review, and current CI once marked Ready.

    493 GitHub stars~2.1k tokensUpdated today
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  • Self Review

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    493 GitHub stars~740 tokensUpdated today
    Auto-check passed
  • Independent Review

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Questions about Self Review Round Two

What does Self Review Round Two do?

Run the second PyAthena self-review after round one, auditing factual claims, caller compatibility, AWS operational effects, and evidence from a user's perspective before Ready. Self Review Round Two is an agent skill from pyathena-dev/PyAthena. Run the second PyAthena self-review after round one, auditing factual claims, caller compatibility, AWS operational effects, and evidence from a user's perspective before Ready.

When should I use Self Review Round Two?

Self Review Round Two fits situations like: databases work in your project.

How do I install Self Review Round Two in Claude Code?

Run `npx skills add pyathena-dev/PyAthena --skill self-review-round-two -a claude-code`. Or copy the skill folder (.agents/skills/self-review-round-two in pyathena-dev/PyAthena) into .claude/skills/self-review-round-two in your project. Claude Code loads it when a task matches its description.

How do I install Self Review Round Two in Codex?

Run `npx skills add pyathena-dev/PyAthena --skill self-review-round-two -a codex`. Or copy the skill folder (.agents/skills/self-review-round-two in pyathena-dev/PyAthena) into .agents/skills/self-review-round-two in your project. Codex loads it when a task matches its description.

Can I use Self Review Round Two in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pyathena-dev/PyAthena --skill self-review-round-two -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/self-review-round-two, .gemini/skills/self-review-round-two, .github/skills/self-review-round-two and .opencode/skills/self-review-round-two in your project.

What does Self Review Round Two need to run?

SKILL.md names no scripts, command-line tools or credentials: Self Review Round Two is instructions for the agent only.

Does Self Review Round Two access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Self Review Round Two safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Self Review Round Two use?

Self Review Round Two is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Self Review Round Two use?

About 820 tokens (SKILL.md is roughly 3.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Self Review Round Two?

Skills that share tags, products or a category with Self Review Round Two: Mastering Python Skill (SpillwaveSolutions/agent-brain, 119 stars), AWS Dynamodb (alinaqi/maggy, 707 stars), Using Relational Databases (ancoleman/ai-design-components, 526 stars) and AWS SDK Python Usage (aws/agent-toolkit-for-aws, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Self Review Round Two?

pyathena-dev (a GitHub organization) maintains it in pyathena-dev/PyAthena, which has 493 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 9, 2026.

Source: pyathena-dev/PyAthena on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.