Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/arrrrny/zuraffa/speckit.bug.fetchgit clone --depth 1 https://github.com/arrrrny/zuraffaWrote 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/commands/arrrrny/zuraffa/speckit.bug.fetch)<a href="https://agentmods.dev/commands/arrrrny/zuraffa/speckit.bug.fetch"><img src="https://agentmods.dev/badge/commands/arrrrny/zuraffa/speckit.bug.fetch.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.02137 |
| Opus 5 | $0.00012 | $0.01069 |
| Sonnet 5 | $0.00005 | $0.00427 |
| Haiku 4.5 | $0.00002 | $0.00214 |
Grade A, and why
speckit.bug.fetch 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 4d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fetch Bug (Load Existing Issue)
Load an existing GitHub issue into the local bug workflow. This is the complement of __SPECKIT_COMMAND_BUG_ISSUE__, which creates an issue — fetch loads one that already exists. It pulls the issue via the gh CLI, records it at .specify/bugs/<slug>/issue.md, and seeds .specify/bugs/<slug>/assessment.md so the rest of the pipeline (__SPECKIT_COMMAND_BUG_FIX__, __SPECKIT_COMMAND_BUG_TEST__) can proceed.
Use fetch when a bug is already tracked on GitHub (reported by someone else, or from another session) and you want to triage and fix it here. fetch never creates, edits, or closes the issue — it only reads it.
User Input
$ARGUMENTS
Accept any of:
- An issue number (e.g.
1234) — resolved against the current repository. - A URL (e.g.
https://github.com/<owner>/<repo>/issues/1234). - An
owner/repo#numberreference (e.g.github/spec-kit#1234). - An explicit slug via
slug=<bug-slug>/--slug <bug-slug>(optional; otherwise derived from the issue title).
Slug Resolution
Each bug gets its own directory under .specify/bugs/<slug>/. If the user passed a slug, use it verbatim after normalization (lowercase, hyphen-separated, no spaces, no special characters other than - and digits). Otherwise derive a 2–4 word kebab-case slug from the issue title. Ensure the directory is unique — if .specify/bugs/<slug>/ already exists, append the shortest disambiguating suffix (-2, -3, …) or -<issue-number>. Never overwrite an existing bug directory.
After resolution, set BUG_SLUG and BUG_DIR = .specify/bugs/<BUG_SLUG>.
Prerequisites
- Ensure
.specify/bugs/<BUG_SLUG>/exists (create it, including any missing parents, if necessary). - If
BUG_DIR/issue.mdalready exists, do not re-fetch silently: report the existing link and stop (unless the user explicitly asks to refresh). If they ask to refresh, overwriteissue.md; never clobberassessment.md/fix.md/test.md— only regenerateassessment.mdif it is missing or with explicit confirmation. - Detect GitHub context (same as
__SPECKIT_COMMAND_BUG_ISSUE__):git rev-parse --is-inside-work-tree 2>/dev/nullto confirm a repository.git config --get remote.origin.urlto read the remote; parseowner/repo(HTTPShttps://github.com/<owner>/<repo>.gitor SSH[email protected]:<owner>/<repo>.git). Only proceed with a live fetch when the remote points togithub.com.command -v gh >/dev/null 2>&1andgh auth statusto confirm the CLI and auth. Ifgh/GitHub remote/auth is unavailable, skip the live fetch and write a draft (see Graceful Degradation).
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.
- 4d ago First seen · 148 lines · 23 tokens per session scan A 02117428f85e
speckit.bug.fetch is a command published in the GitHub repository arrrrny/zuraffa (5 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 2,137 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
building-flutter-apps-skill-ac1294fc
Flutter Riverpod app architecture and Windows installer delivery. Use before changing a Riverpod Flutter app/package or its Windows desktop packaging/update pipeline; skip non-Riverpod stacks and pure-Dart work.
Generate Implementation Plan
Create intelligent, dependency-aware implementation plan with sprint planning and team allocation.
Analyze Feature Dependencies
Map feature dependencies and suggest optimal implementation order.
Auto-Generate PRD from All Project Files
Automatically discover and consolidate all markdown files in project into comprehensive PRD.
Analyze PRD
Validate and analyze PRD with quality scoring, show customizations.
Refine PRD
Interactively improve PRD quality through AI-guided analysis and refinement.