Source profileQuality 70/100

dyoshikawa/rulesync/.rulesync/skills/post-issue-comment/SKILL.md

post-issue-comment

Post a reply comment on a GitHub issue in English with a natural, concise writing style, based on the intent passed as arguments

Source repository stars
1,263
Declared platforms
0
Static risk flags
0
Last source update
2026-07-28
Source checked
2026-07-28
DecisionCompatibilityInstallWorkflowPermissionsEvidenceSource

Decision brief

What it does—and where it fits

Run the following in parallel:

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/dyoshikawa/rulesync --skill ".rulesync/skills/post-issue-comment"
    Safe inspection promptEditorial

    Inspect the Agent Skill "post-issue-comment" from https://github.com/dyoshikawa/rulesync/blob/310b711fbe8cffc14debb276ade8a384c2b89083/.rulesync/skills/post-issue-comment/SKILL.md at commit 310b711fbe8cffc14debb276ade8a384c2b89083. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Step 1: Gather Issue Context

      Run the following in parallel:

      Get the issue description and metadata: gh issue viewGet the issue comments: gh issue view --commentsRun the following in parallel:
    2. 02

      Step 2: Draft the Reply

      Based on the issue content and the user's intent, draft a reply comment.

      Ground the reply in the actual discussion — address the latest comment or the original issue as appropriate.Reflect the user's intent faithfully; do not add positions the user did not ask for.If relevant context is missing or a decision cannot be made without more information, say so in the reply rather than guessing.
    3. 03

      Step 3: Post the Comment

      Post the drafted reply using:

      Post the drafted reply using:
    4. 04

      Step 4: Report

      Output the issue number and a brief summary of the comment that was posted.

      Output the issue number and a brief summary of the comment that was posted.

    Permission review

    Static risk signals and limitations

    No configured static risk pattern was detected

    This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score70/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars1,263SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    dyoshikawa/rulesync
    Skill path
    .rulesync/skills/post-issue-comment/SKILL.md
    Commit
    310b711fbe8cffc14debb276ade8a384c2b89083
    License
    MIT
    Collected
    2026-07-28
    Default branch
    main
    View the original SKILL.md

    arguments = the user's request

    Parse arguments as:

    • target_issue: the issue number (or URL) to reply to
    • intent: the gist of the reply the user wants to post (what to say, the stance to take, the points to cover)

    If target_issue is not provided, ask the user which issue to comment on. If intent is not provided, ask the user what the reply should convey.

    Step 1: Gather Issue Context

    Run the following in parallel:

    • Get the issue description and metadata: gh issue view <issue_number>
    • Get the issue comments: gh issue view <issue_number> --comments

    If the issue references related pull requests, commits, or files that are needed to craft an informed reply, gather that context as well.

    Step 2: Draft the Reply

    Based on the issue content and the user's intent, draft a reply comment.

    • Ground the reply in the actual discussion — address the latest comment or the original issue as appropriate.
    • Reflect the user's intent faithfully; do not add positions the user did not ask for.
    • If relevant context is missing or a decision cannot be made without more information, say so in the reply rather than guessing.

    Step 3: Post the Comment

    Post the drafted reply using:

    gh issue comment <issue_number> --body "<reply body>"

    Writing Style

    Write in English only.

    Style guidelines — write like a human teammate, not a bot:

    • Use plain paragraphs. Avoid headings (##), horizontal rules (---), and excessive bullet lists.
    • Keep it conversational and direct. Say what matters, skip the filler.
    • Do not use phrases like "Great point!" or "Thanks for raising this!" unless you genuinely mean it and have nothing else to add.
    • Be honest. If you disagree or see an issue, say so clearly but respectfully.
    • Short is fine. A two-sentence comment is better than a five-paragraph essay with no substance.

    Step 4: Report

    Output the issue number and a brief summary of the comment that was posted.

    Alternatives

    Compare before choosing

    Computed 10042,015

    coreyhaines31/marketingskills

    ab-testing

    When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program

    2026-07-270 platforms
    Computed 10042,015

    coreyhaines31/marketingskills

    churn-prevention

    When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers o

    2026-07-270 platforms
    Computed 997

    event4u-app/agent-config

    design-review

    Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.

    2026-07-280 platforms
    Computed 9831,966

    K-Dense-AI/scientific-agent-skills

    dask

    Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.

    2026-07-280 platforms