agentleFS
rikilamadridrikilamadrid/pathfinder/skills/ticket/SKILL.md

ticket

Skill1 starsChanged 43 days agoMITView on GitHub

Run one action of the ticket delivery loop — load, start, adversary, review, or complete.

23 other projects use a version of this, 1 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use retro, spec and 4 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • AWSSkill

    retro

    Conduct a retrospective on a coding session.

    Also in 3 projects that use this

  • SentrySkill

    spec

    Produce a verified spec — problem, desired outcome, and acceptance criteria — before building. Use when given a GitHub/Linear issue link, when starting from a fuzzy in-conversation idea, or asked to "figure out what to do" / "scope this" / "what should I build" — whenever the *what* isn't yet pinned down. Grills the ambiguities, checks the premise against the code, and produces acceptance criteria you sign off on — then hands to design-first.

    Also in 3 projects that use this

  • AWSSkill

    ship

    Finalize dev work on an issue branch — update docs, push, and open a PR.

    Also in 3 projects that use this

  • Microsoft AzureSkill

    verify

    End-to-end app testing pipeline for browser-based web apps on cloud browsers via Azure Playwright Workspaces: verify the live app, author tests for working flows, heal failing tests, then re-run with video and produce one consolidated report. Three phases (app verification, test authoring, test healing) plus a scoped final sanity run; each phase emits a sub-report. Use when asked to "verify my app", "make sure my app works and has good test coverage", "do a full QA pass", "add tests where I'm missing coverage", "fix failing tests and add new ones", "smoke test before deploy", "QA my deployment", or any combined verify-and-test ask. Requires Azure CLI (`az login`) and a Playwright Workspace resource ID — bootstraps configs on first invocation. Browser-based web apps with Playwright only — not for unit/API tests, native mobile/desktop, load/perf, or full accessibility audits.

    Also in 3 projects that use this

  • SentrySkill

    review

    Fixture review skill.

    Also in 3 projects that use this

  • GoogleSkill

    tdd

    Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

6 rules. 0 are common, 4 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 20 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If none was given, list the five actions below and stop.

    line 20
  2. Distinctive:

    If it is not one of the five, say so, list them, and stop.

    line 21
  3. Very specific:

    Read only skills/ticket/actions/<action>.md and follow it exactly.

    line 22
  4. Very specific:

    Every reader of the mode — the actions below, whereami, and the session orientation handler — reads it this way, and nothing else restates …

    line 77
  5. Distinctive:

    Run the one action the human named.

    line 98
  6. Distinctive:

    Read only that action's file.

    line 99

“Common” is measured: kept by at least 6 in 10 of the 20 edited versions of this file we could read. “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

Ticket

The delivery loop, as one skill. The human names the action:

/ticket load <ticket> /ticket start /ticket adversary /ticket review /ticket complete [<ticket>]

Process

  1. Take the action from the invocation. If none was given, list the five actions below and stop. If it is not one of the five, say so, list them, and stop.
  2. Read only skills/ticket/actions/<action>.md and follow it exactly.

Actions

  • load — prepare one ticket for execution. Resolves the ticket store, reads the ticket and its parent Feature spec, verifies every blocker, loads the minimum context the ticket names, and writes the session's workspace state.
  • start — implement the loaded ticket, restating the pre-implementation summary before editing anything.
  • adversary — optionally challenge one implemented ticket through bounded, reproducible experiments. It gives no verdict, changes no lifecycle status, and hands suspected defects to Tester.
  • review — verify implemented work against the ticket and its parent Feature, and report findings. It changes no implementation and accepts nothing.
  • complete — complete work the human has accepted, through the project's delivery workflow and its durable records, then name the tickets that are now ready.

Lifecycle

A ticket's status holds the durable lifecycle state named in context/ai-interaction.md. It lives in the ticket store — see skills/ticket/store.md, which is where the store and ticket identity are defined:

Proposed → Ready → In Progress → Complete

Cancelled and Superseded are terminal alternatives.

  • load writes Proposed → Ready.
  • start writes Ready → In Progress.
  • complete writes Complete.
  • adversary writes no status.
  • review writes no status. Review is workflow activity, not lifecycle state.

The parent Feature's status is derived from its tickets, never maintained by hand. start and complete are the only actions that write it, and each writes it only as a consequence of the ticket transition it just made.

context/current-ticket.md is transient workspace state and records no status.

Execution mode

A project records how Pathfinder runs it in context/execution-mode.md, on one marker line:

<!-- pathfinder:execution-mode <value> -->

The values are human-in-the-loop and orchestrator. No file means human-in-the-loop; every project installed before the file existed is one, and nothing needs migrating. A file whose marker is missing or names anything else is invalid: report it once, naming the file and the two values, and proceed as human-in-the-loop. Never infer a mode from prose, the environment, or the harness.

Every reader of the mode — the actions below, whereami, and the session orientation handler — reads it this way, and nothing else restates it. In human-in-the-loop mode nothing in this skill behaves differently from before the file existed.

Full-suite reuse

A role may cite a full-suite run it made earlier instead of running the suite again only when all of these hold: the same role made it, in the same session; HEAD is unchanged and git status --porcelain was empty at that run and is empty now; that run exited 0; and no dependency, lockfile, environment, or install change has happened since. The citation is one line, suite: <command> | head <sha> | clean | exit 0 | <counts> | <UTC time>. A dirty tree is never reused. These always run fresh: focused tests after an edit; any run after a change; a run by another role or in another session, which is never cited; the Tester's own run at the Developer's head; Adversary experiments; CI; complete's final checks (its step 1), whether they run pre-merge or post-merge; and any re-run after a failure.

Rules

  • Run the one action the human named. Do not continue into the next one.
  • Read only that action's file. The other actions are not context for this work.
  • One ticket at a time. A session that finishes a ticket stops there.
  • Human authority is unchanged: approval, acceptance, merge, and release are the human's, whichever action is running.

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.