Runs a list of HTTP checks against a base URL from a JSON file and reports status codes, response time and body assertions. Use when the user asks whether an API is up, wants a smoke test after a deploy, or needs to verify that endpoints return what the docs promise.
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Turns git log output into a grouped markdown changelog using conventional commit prefixes such as feat, fix and docs. Use when the user prepares a release, asks for release notes, or wants a summary of what changed between two tags.
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Writes clear git commit messages in the conventional commits style from a diff or a description of the change. Use when the user asks for a commit message, wants to tidy up a message before pushing, or has staged changes and no wording yet.
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Profiles a CSV file column by column, reporting inferred type, missing values, unique counts and min, max and mean for numeric columns. Use when the user hands over a CSV and asks what is in it, whether the data is clean, or what to check before analysis.
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Checks a Dockerfile for common problems such as unpinned base images, running as root, ADD instead of COPY, secrets in ENV or ARG and apt-get without cleanup. Use when the user asks to review, harden or slim down a Dockerfile.
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Compares a .env file with its .env.example template and reports missing keys, undocumented extra keys, empty values and example files that contain real looking secrets. Use when the user asks why an app fails on startup with missing configuration, or wants to check environment files before committing.
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Compares two JSON files structurally and lists added, removed and changed values with their full paths. Use when the user asks what changed between two API responses, config files, fixtures or package manifests.
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Summarizes application log files by severity, time range and the most frequent error messages. Use when the user shares a log file or pasted log output and asks what went wrong, which errors repeat, or how noisy the log is.
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Converts raw meeting notes or a transcript into decisions, action items with owners and due dates, and open questions. Use when the user pastes meeting notes, asks for a summary of a call, or wants a follow-up message for attendees.
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Drafts a pull request description with a summary, motivation, a change list, test notes and risks from a diff or commit list. Use when the user opens a pull request, asks for a PR description, or wants reviewers to understand a change quickly.
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Finds common Python code smells with the ast module, such as bare except clauses, mutable default arguments, missing docstrings, very long functions and long argument lists. Use when the user asks for a quick review of Python code, a cleanup pass or a pre-commit style check.
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Reviews a README for the things that make people try a project, covering the opening line, install steps, a runnable example, proof that it works and contribution info, then proposes concrete edits. Use when the user asks to improve a README, wants more stars or users for an open source project, or is preparing a launch.
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Reviews code for common security flaws such as injection, broken authentication, unsafe deserialization, hardcoded secrets, path traversal and weak cryptography, and reports findings with severity and fixes. Use when the user asks for a security review, a pre-release audit or a check of code that handles user input, files or credentials.
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Guides an agent through writing a good SKILL.md, covering the name, a description that triggers at the right time, concise instructions, bundled scripts and tests. Use when the user asks to create, improve or review an agent skill, or wants to turn a repeated task into a reusable skill.
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Reviews SQL queries for correctness, performance and safety problems such as SELECT star, missing indexes, unbounded updates, implicit casts and injection risks. Use when the user asks to optimize a query, explain why a query is slow, or check SQL before it runs on production data.
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Finds TODO, FIXME, HACK and XXX comments across a source tree and groups them by tag and file. Use when the user asks for a list of open tasks in the code, wants to plan cleanup work, or needs an inventory of technical debt.
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Lets a Hermes agent turn a task it keeps repeating into a tested, reusable skill, using askit to lint, scan, test and score the result before sharing it. Use when the same kind of request comes up more than twice, or when the user asks the agent to save a workflow as a skill.
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