agentleFS
equinorequinor/fusion-skills/skills/.experimental/fusion-issue-solving/SKILL.md

fusion-issue-solving

Skill2 starsChanged 2 months agoMITView on GitHub

Handles GitHub issue resolution end-to-end for prompts like "solve #123", "lets solve #123", "work on #123", "work on https://github.com/owner/repo/issues/123", or by pasting a direct GitHub issue URL as the request. USE FOR: solve #123, continue work on issue #123, work on https://github.com/owner/repo/issues/123, paste a GitHub issue URL for implementation work. DO NOT USE FOR: issue drafting only, PR review only, or non-implementation research.

The file

Show its rules and text

We split this skill into the rules it gives an agent

35 rules. About 0 are common, 29 are distinctive, and 6 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈29

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use when the user wants to solve or continue a GitHub issue end-to-end, including short current-repo prompts like solve #123, direct GitHub …

    line 27
  2. Very specific:

    Treat GitHub issue URLs as interchangeable with #123 references for verbs like solve, fix, implement, continue, finish, or work on.

    line 40
  3. Distinctive:

    No implementation changes expected

    line 45
  4. Distinctive:

    Ask whether to use a dedicated git worktree

    line 63
  5. Distinctive:

    Ask this before any other workflow questions.

    line 64
  6. Distinctive:

    If yes, use/create the worktree and continue there.

    line 65
  7. Distinctive:

    Read the issue body, labels, and linked discussions once, then reuse that context instead of refetching.

    line 68
  8. Distinctive:

    Check whether the current user is assigned to the primary issue.

    line 72
  9. Distinctive:

    If the current user is not assigned, ask whether they want to assign themselves before continuing.

    line 73
  10. Distinctive:

    If the current user is not assigned on a sub-issue, ask whether they want to assign themselves before resolving/closing it.

    line 75
  11. Very specific:

    Prefer MCP-backed tools over ad hoc gh api or GraphQL calls when equivalent tools exist.

    line 78
  12. Distinctive:

    Avoid duplicate lookups for labels, issue types, and duplicate detection.

    line 79
  13. Very specific:

    When delegating to fusion-issue-authoring or its subordinate skills, the orchestrator's session-cache rules apply: labels and assignee …

    line 81
  14. Distinctive:

    Use GraphQL fallback only when MCP coverage is unavailable and do not loop retries.

    line 82
  15. Distinctive:

    If rate limits are hit, stop non-essential operations and continue with local implementation/PR preparation when possible.

    line 86
  16. Distinctive:

    Create actionable todos ordered by dependencies.

    line 89
  17. Distinctive:

    Keep exactly one step in progress and update status as work completes.

    line 90
  18. Distinctive:

    Prefer root-cause fixes over surface patches.

    line 94
  19. Distinctive:

    Keep each change aligned to issue acceptance criteria.

    line 97
  20. Distinctive:

    Avoid unrelated refactors and generated release artifacts.

    line 98
  21. Distinctive:

    Run targeted checks first, then required project checks.

    line 101
  22. Distinctive:

    If checks fail, fix relevant issues and re-run before proceeding.

    line 102
  23. Distinctive:

    Ask which base branch to target and propose a likely default (typically main, or the branch the current branch was cut from).

    line 109
  24. Distinctive:

    Ask whether the PR should be opened as draft or ready for review.

    line 110
  25. Distinctive:

    Ask whether the PR should be assigned to the user and whether related issues should be linked.

    line 111
  26. Very specific:

    Before any GitHub mutation (create/edit/comment/close), ask for explicit user confirmation.

    line 114
  27. Distinctive:

    If requested, update issue status/comments with objective progress.

    line 115
  28. Distinctive:

    Prefer MCP tool mutations over ad hoc API calls when equivalent operations exist.

    line 116
  29. Distinctive:

    If GitHub API rate limits block mutation, report the failure clearly, stop retry loops, and propose a safe retry sequence.

    line 117
  30. Very specific:

    If requested, create or update the PR using the repository PR template and the .tmp/ PR body draft file, using the confirmed base branch, …

    line 118
  31. Distinctive:

    Never request or expose secrets/credentials.

    line 138
  32. Distinctive:

    Never run destructive commands without explicit confirmation.

    line 139
  33. Distinctive:

    Keep changes minimal and scoped to the issue.

    line 140
  34. Distinctive:

    Do not claim checks passed without running them.

    line 141
  35. Distinctive:

    Follow repository instructions and contribution rules.

    line 142

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Issue Solving Workflow

When to use

Use when the user wants to solve or continue a GitHub issue end-to-end, including short current-repo prompts like solve #123, direct GitHub issue URLs, or requests like lets work on https://github.com/owner/repo/issues/123.

Typical triggers:

Treat GitHub issue URLs as interchangeable with #123 references for verbs like solve, fix, implement, continue, finish, or work on. A direct GitHub issue URL can serve as the main request payload when no competing intent is stated.

When not to use

  • Request is only issue drafting/authoring
  • No implementation changes expected
  • Repository write operations are disallowed

Required inputs

Collect before execution:

  • issue URL or owner/repo#number
  • repository and branch/worktree decision
  • acceptance criteria and out-of-scope constraints
  • required validation commands for the target repository

Optional:

  • related issues/PRs
  • risk areas to prioritize
  • requested commit/PR granularity

Instructions

  1. Ask whether to use a dedicated git worktree
    • Ask this before any other workflow questions.
    • If yes, use/create the worktree and continue there.
  2. Confirm issue context and success criteria
    • Read the issue body, labels, and linked discussions once, then reuse that context instead of refetching.
    • Restate the implementable scope and explicitly list out-of-scope items.
  3. Confirm assignee intent for issue closure work
    • Check whether the current user is assigned to the primary issue.
    • If the current user is not assigned, ask whether they want to assign themselves before continuing.
    • For each sub-issue that will be resolved or closed by this workflow, check assignee status once and reuse the result for closure decisions.
    • If the current user is not assigned on a sub-issue, ask whether they want to assign themselves before resolving/closing it.
  4. Apply low-token GitHub strategy
    • Prefer MCP-backed tools over ad hoc gh api or GraphQL calls when equivalent tools exist.
    • Avoid duplicate lookups for labels, issue types, and duplicate detection.
    • Cache per-run context (issue metadata, duplicate matches, issue-type support, label sets, assignee candidates) and reuse it — do not re-fetch data that was already retrieved in this session.
    • When delegating to fusion-issue-authoring or its subordinate skills, the orchestrator's session-cache rules apply: labels and assignee candidates are fetched once per repository, issue types once per organization.
    • Use GraphQL fallback only when MCP coverage is unavailable and do not loop retries.
    • GraphQL mutations cost 5 secondary-limit points each (vs 1 for queries); batch fields into single calls and pause at least 1 second between mutation calls.
    • Budget awareness: a typical implementation session (read issue + duplicate check + 1–2 mutations + sub-issue links) should stay under ~20 MCP read calls and ~5 mutations. If the running total approaches 30+ calls, pause optional enrichment and proceed with local work.
    • Respect retry-after and x-ratelimit-reset headers; do not retry before the indicated wait.
    • If rate limits are hit, stop non-essential operations and continue with local implementation/PR preparation when possible.
  5. Build and track a concrete plan
    • Create actionable todos ordered by dependencies.
    • Keep exactly one step in progress and update status as work completes.
  6. Research before edits
    • Inspect relevant files, tests, and adjacent usage.
    • Prefer root-cause fixes over surface patches.
  7. Implement in small scoped changes
    • Keep each change aligned to issue acceptance criteria.
    • Avoid unrelated refactors and generated release artifacts.
  8. Validate incrementally
    • Run targeted checks first, then required project checks.
    • If checks fail, fix relevant issues and re-run before proceeding.
  9. Prepare PR-ready output
    • Summarize what changed and why.
    • Include validation evidence and known follow-ups.
    • Draft the PR body in a .tmp/ file with an issue/context-specific name (for example, .tmp/pr-body-issue-123-scope-summary.md), not a shared .tmp/pr-body.md.
    • Base the draft on .github/pull_request_template.md and keep it updated as implementation evolves.
    • Ask which base branch to target and propose a likely default (typically main, or the branch the current branch was cut from).
    • Ask whether the PR should be opened as draft or ready for review.
    • Ask whether the PR should be assigned to the user and whether related issues should be linked.
  10. Optional GitHub mutation steps
  • Before any GitHub mutation (create/edit/comment/close), ask for explicit user confirmation.
  • If requested, update issue status/comments with objective progress.
  • Prefer MCP tool mutations over ad hoc API calls when equivalent operations exist.
  • If GitHub API rate limits block mutation, report the failure clearly, stop retry loops, and propose a safe retry sequence.
  • If requested, create or update the PR using the repository PR template and the .tmp/ PR body draft file, using the confirmed base branch, draft/ready state, assignee choice, and related issue links.

Expected output

Return a concise delivery report with:

  • implemented scope vs original issue criteria,
  • files changed,
  • validation commands and outcomes,
  • assignment decisions for primary issue and affected sub-issues,
  • API usage strategy used (MCP-first/cache reuse/fallbacks),
  • open risks/blockers,
  • PR body summary (or .tmp/ draft file path when created).

Assets

  • assets/issue-solving-checklist.md

Safety & constraints

  • This skill is mutation-capable. Repository-local workflow instructions take precedence over inline guidance when they conflict.
  • Never request or expose secrets/credentials.
  • Never run destructive commands without explicit confirmation.
  • Keep changes minimal and scoped to the issue.
  • Do not claim checks passed without running them.
  • Follow repository instructions and contribution rules.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.