Borrowing it
Nothing to install: this file belongs to w00fx/spec-anchored-agentic-development. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/w00fx/spec-anchored-agentic-development/main/.agents/skills/spec-to-tickets/SKILL.mdgit clone --depth 1 https://github.com/w00fx/spec-anchored-agentic-developmentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/w00fx/spec-anchored-agentic-development/spec-to-tickets)<a href="https://agentmods.dev/skills/w00fx/spec-anchored-agentic-development/spec-to-tickets"><img src="https://agentmods.dev/badge/skills/w00fx/spec-anchored-agentic-development/spec-to-tickets/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/w00fx/spec-anchored-agentic-development/spec-to-tickets"><img src="https://agentmods.dev/badge/skills/w00fx/spec-anchored-agentic-development/spec-to-tickets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.02604 |
| Opus 5 | $0.00019 | $0.01302 |
| Sonnet 5 | $0.00008 | $0.00521 |
| Haiku 4.5 | $0.00004 | $0.00260 |
Grade A, and why
spec-to-tickets scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Convert one effective capability spec into a reviewed set of implementation issues. You may inspect the repository and publish or update issues. Do not modify production code or the capability spec.
Core law
One issue is one delivery task:
the smallest coherent unit that produces one meaningful, independently demonstrable outcome and justifies one owner, one branch, at most one PR, and one complete implementation-to-review lifecycle.
Optimize for cohesion and coordination cost, not for the smallest technically separable change.
Do not equate these units:
requirement ID durable truth in the spec
issue / task coherent delivery outcome
implementation step work inside the task's plan
verification case evidence proving the task
specialist pass mutation, QA, hardening, or review inside the task
One task may implement and verify many stable IDs, cross several layers, contain several test types, and use multiple fresh specialist agents.
1. Pin truth and inspect the seam
Read the complete capability spec and its canonical companion files. Resolve the exact committed revision that makes it effective on the protected/default branch.
Every task records:
capability ID
spec path
spec commit
stable IDs implemented and verified
If the spec is not effective, stop with SPEC_NOT_EFFECTIVE.
Inspect the relevant code, contracts, tests, ADRs, and repository conventions. Identify:
- what already exists;
- the missing delivery outcomes;
- explicit milestones and checkpoints;
- shared implementation contexts;
- independent approval, rollout, rollback, migration, experiment, or operational boundaries.
Use capability language in titles and descriptions.
2. Draft outcome-oriented candidates
Use the spec's milestones, checkpoints, vertical validations, independently demonstrable experiments, and lifecycle boundaries as the first candidates. They are candidates, not automatic one-to-one tickets.
Build a milestone/checkpoint reconciliation before finalizing the candidates:
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 342 lines · 38 tokens per session scan A 47bd0a68e4f2
spec-to-tickets is a skill published in the GitHub repository w00fx/spec-anchored-agentic-development (5 stars, last pushed 7d ago), licensed MIT. It adds 38 tokens to every session and 2,604 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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Pipeline dashboard — current feature, position, per-group progress, approvals, pending PRs, blockers. Read-only, any time.
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conductor-new-track
Plans a new track (feature or bug fix), generates spec/plan documents, and updates the registry.
gsd-map-codebase
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gsd-workspace
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gsd-inbox
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