ticket-craft
Skill0 starsChanged 35 days agoMITView on GitHub
Write, refine, or review software epics, user stories, and subtasks for human teams and AI agent handoffs, with shared acceptance criteria and explicit unresolved decisions.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- alinaqi/claude-bootstraptheir own version, first seen Oct 8, 2026
- alinaqi/maggytheir own version, first seen Jun 12, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- alinaqi/maggy★ 711same name
- alinaqi/claude-bootstrap★ 708same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository13 other files it gives its agents.
- advocatus-diaboliSkill
- agentic-harness-engineeringSkill
- agent-instruction-reliabilitySkill
- agent-instructionsSkill
- agent-orchestrationSkill
- context-loadingSkill
- context-managementSkill
- copilot-usage-baselineSkill
- learning-loopSkill
- research-to-skillSkill
- skill-refinementSkill
- stateful-evidence-reasoningSkill
- technical-documentationSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 7
Create descriptions that explain the purpose to people and give an executor enough information to act and verify the result.
- Distinctive: line 15
Read templates when drafting.
- Distinctive: line 23
Keep outcome measurement distinct from delivery acceptance.
≈ “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.
Files
Ticket Craft
Create descriptions that explain the purpose to people and give an executor enough information to act and verify the result. Use one canonical set of requirements; add agent execution context when needed. This shared-core design is an engineering synthesis, not a proven universal format.
Establish the item and its audience
Choose drafting, revision, or review-only from the request. In review-only mode, return findings and suggested corrections without rewriting the descriptions or changing artifacts. For revisions, preserve existing item IDs, links, agreed requirements, and criterion IDs referenced by other items; identify any necessary contract change explicitly.
Use the request and supplied artifacts to identify the item type, intended audience, parent outcome, and stage: discovery, refinement, or execution. Respect local tracker terminology. An epic organizes a larger outcome; a story describes a useful behavior; a subtask contributes a bounded deliverable. Technical enablers and investigations need a concrete beneficiary or decision, not an invented user persona.
Read templates when drafting. Read examples when hierarchy or audience differences need clarification. Read evidence when explaining the basis, evaluating a disputed rule, or refreshing the guidance.
Build the shared description
- Lead with the desired change and why it matters. For a story, name the actor, capability, and benefit in natural language; use “As a …” only when it helps. Keep supporting detail outside the short story sentence.
- Distinguish supplied facts, verified facts, proposed decisions, and open questions. Do not invent metrics, deadlines, owners, interfaces, commands, source paths, or acceptance behavior. A plausible proposal remains a proposal until adopted.
- State the scope and relevant boundaries. Make ambiguous domain terms concrete. Describe constraints as requirements only when supplied or verified; label implementation suggestions separately.
- Make acceptance criteria observable: condition/input, action or event, expected result. Include failure and boundary behavior when they change the accepted solution. Quantified quality requirements need a supplied or agreed threshold, workload, environment, and measurement method; otherwise name the unresolved decision.
- Keep outcome measurement distinct from delivery acceptance. Passing software tests does not demonstrate an epic's business impact. Reference the team's Definition of Done when provided; do not replace it with item-specific criteria.
- Link dependencies and state what they must provide. For a hierarchy, map each child to its parent's outcome or criterion and check gaps, overlaps, and contradictions. Prefer end-to-end story slices when they preserve useful value; internal layer work can be a subtask or enabler. Do not split mechanically on the word “and.”
INVEST and SMART are practitioner review prompts, not evidence-backed pass/fail scoring systems. Preserve real dependencies and negotiable design; do not manufacture independence, estimates, or arbitrary size limits.
Add the agent handoff when requested or needed
An agent executing asynchronously cannot rely on an unwritten conversation. Capture the consequential decisions and add only context that changes execution:
- Starting repository/artifact and version when known; relevant entry points, accessible source links, and why each matters. Verify references when access is available. Label unverified pointers; if a required source is inaccessible, include the necessary supplied excerpt or mark the dependency unresolved.
- Task-specific constraints, allowed discretion, and the authorized deliverable/action boundary. An agent description does not authorize publication, deployment, or unrelated work.
- Relevant verification commands and prerequisites when known. Keep acceptance criteria authoritative; tests should cover them without enforcing unrequested implementation choices. If tools cannot verify a criterion, name the alternate inspection or the remaining limitation.
- Unresolved decisions and recovery: inspect available authoritative artifacts for repository questions; ask the decision owner about missing product behavior that would change correctness. Continue independent drafting, but do not label that portion executable. Routine implementation choices may remain the executor's discretion.
- Expected completion evidence: artifact/change summary, criterion results, checks actually run, and remaining blockers. A failed environment check is not proof the implementation fails; report what remains unverified.
Keep essential outcome, constraints, and acceptance visible. Link substantial supporting detail with a clear reason to load it. Avoid copying a repository overview or generic workflow into every ticket. Evidence about repository context files and older retrieval models does not establish an optimal ticket length or guarantee current-agent performance.
Review and deliver
Use review checks before finishing. For drafting or revision, return the description(s), any consequential questions, and a concise readiness judgment: discovery, needs refinement, or ready for the stated executor with disclosed limitations. These are descriptive judgments, not mandatory workflow gates. A human-readable discovery epic need not contain implementation instructions. An agent tasked only with analysis needs an analysis deliverable, not a fabricated coding plan.
For reviews, identify the source location, exact ambiguity or inconsistency, its execution consequence, and a suggested correction. If no material defect is found, report that with review limits rather than manufacturing findings. Preserve existing intent. Writing descriptions does not execute the work or update a live tracker unless requested.
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
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.

