Към всички skills

1-triage-issues

stickerdaniel · Инструменти

Triage backlog, scan open issues, rank what to tackle first, or which PRs are production-ready.

Оригинален текст · няма потвърден превод на български

Теми: ai-agents · anthropic · chatgpt · chatgpt-desktop · claude · claude-ai · claude-code · claude-desktop · desktop-extension · dxt · linkedin · linkedin-api · linkedin-mcp · linkedin-profile-scraper · linkedin-scraper

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Оригинален SKILL.md
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Apache-2.0
Последна проверка на записа
22.09.2026 г.

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npx skills add stickerdaniel/linkedin-mcp-server

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Откъс от SKILL.md

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Triage open issues and PRs

Turn the live state of stickerdaniel/linkedin-mcp-server into a maintainer priority list. Read-only. No checkout, no labels, no comments, no closure, no reproduction.

Reproduction belongs in /2-repro-issue. PR verification belongs in /3-verify-pr-fix.

Inputs

$ARGUMENTS is optional. If set, treat as a label name (bug, enhancement) or freetext filter. Otherwise scan everything open.

1. Gather

REPO=stickerdaniel/linkedin-mcp-server

# Issues  (gh calls the reactions field `reactionGroups`, not `reactions`)
gh issue list --repo $REPO --state open --limit 200 \
  --json number,title,labels,createdAt,updatedAt,author,comments,reactionGroups,body

# PRs
gh pr list --repo $REPO --state open --limit 100 \
  --json number,title,labels,createdAt,updatedAt,author,mergeable,mergeStateStatus,statusCheckRollup,additions,deletions,changedFiles,reviewDecision,isDraft,headRepositoryOwner

# Cross-link issues ↔ PRs via body references
gh search prs --repo $REPO --state open --json number,body,title --limit 100

Build a map issue_number → [referencing_pr_numbers] by scanning PR bodies for Closes #, Fixes #, Resolves #, plain #N.

If $ARGUMENTS is given, filter both lists before scoring.

Read each issue body and its comments, including linked canonical issues.

2. Packet admission

Before severity, age, reach, or contributor ranking, classify every open issue.

Packet stateMaintainer action
Material evidence missingRecommend needs more info with the specific missing fields. Exclude it from the reproduction shortlist. Existing labels alone do not prove completeness.
Evidence supplied after a requestRead the new evidence. Recommend removing needs more info only when it resolves the material gap. A new comment does not automatically clear the label.
Same underlying report as a canonical issueNote unique reviewed evidence for the canonical issue. Recommend a Duplicate of #N comment and a separate close, each with an explicit yes. Do not post or close here.
Evaluable bug or featureContinue to scoring. Completeness is not a promise of implementation.
Source evidence supports a narrower claim than the reporter's explanationState that narrower finding. Ask for targeted missing evidence only if the next decision needs it.

Целият SKILL.md в GitHub