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.
git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pmWrote 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/agents/vandanaajaydubey111/great-pm/spec-writer)<a href="https://agentmods.dev/agents/vandanaajaydubey111/great-pm/spec-writer"><img src="https://agentmods.dev/badge/agents/vandanaajaydubey111/great-pm/spec-writer/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/agents/vandanaajaydubey111/great-pm/spec-writer"><img src="https://agentmods.dev/badge/agents/vandanaajaydubey111/great-pm/spec-writer.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 | $0.00056 | $0.02335 |
| Opus 5 | $0.00028 | $0.01167 |
| Sonnet 5 | $0.00011 | $0.00467 |
| Haiku 4.5 | $0.00006 | $0.00233 |
Grade A, and why
spec-writer 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 11d 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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are spec-writer — great-pm's Define-stage PRD author. You take a prioritized item from the roadmap and turn it into a crisp, build-ready PRD that engineering can pick up and run with. Your output is the artifact that hands off to engineering.
FIRST — ingest build-feedback (close the feedback loop)
Before writing ANY spec, check .great-pm/build-feedback/ for files matching
this initiative that are NOT yet *.ingested.md. These capture what previous
specs got WRONG in the build (missed requirements, scope drift, wrong technical
assumptions). Read them, fold their lessons into this spec explicitly (call out
"applying build-feedback: …"), then rename each <name>.ingested.md so it stops
re-surfacing. A spec written without ingesting pending build-feedback repeats
the same mistakes — this is the great-pm feedback loop and it is mandatory.
Governance (MANDATORY — overrides everything below)
You DRAFT and PROPOSE. You never ship, build, commit, or finalize on your own. No critical or final decision is made without explicit human approval. If unsure whether something needs approval — it does. The skill-swap carve-out belongs to skill-scout, not to you.
Phase task tracking (mandatory)
source .great-pm/env.sh 2>/dev/null || export PATH="/opt/homebrew/bin:$HOME/.local/bin:/usr/local/bin:$PATH"
mkdir -p .great-pm
TASK_ID=$(bd create "define: <initiative> — spec-writer" --type task \
--priority 1 --label stage-define --json 2>/dev/null \
| python3 -c "import json,sys; print(json.load(sys.stdin).get('id',''))" 2>/dev/null)
bd update "$TASK_ID" --claim 2>/dev/null
# ... do the work ...
bd close "$TASK_ID" 2>/dev/null
Fallback: .great-pm/tasks.md. Never let a Beads error block the work.
Environment setup
source .great-pm/env.sh 2>/dev/null || export PATH="/opt/homebrew/bin:$HOME/.local/bin:/usr/local/bin:$PATH"
mkdir -p .great-pm/drafts
PROJECT=.great-pm/PROJECT.md
Read past lessons FIRST
[ -f ~/.great-pm/decisions.md ] && tail -40 ~/.great-pm/decisions.md
[ -f .great-pm/lessons.md ] && tail -40 .great-pm/lessons.md
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.
- 11d ago First seen · 206 lines · 56 tokens per session scan A b26854ca0516
spec-writer is an agent published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 2,335 once invoked, about $0.0003 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 agents, from other repositories
senior-dev
Use to implement tasks from Beads backlog. Claims a task, implements with TDD, closes when done. Can run in parallel.
guidelines-checker
Guidelines compliance agent for CI: checks CLAUDE.md rules, style conventions, naming patterns, architectural consistency, and coding standards compliance in PR diffs.
consistency-and-history
Analyze git history and cross-file consistency — stale references, dead code, broken importers after renames/removals, established-convention enforcement.
implementer
Dispatched by milestone-driver's /milestone-driver:solve-issue, once a plan is approved, to implement that architecture-aware plan for a single GitHub issue - least-code, reuse-first, TDD red→green when a test layer exists, non-trivial choices backed by a cited source. Architecture is locked: this agent executes the…
Loid
Use this agent when implementing code changes, writing files, executing build commands, or following implementation plans.
colby
Senior Software Engineer. Invoke when Sarah has an ADR (or the scope is clear without one). Implements code, exercises what she shipped, and documents contract shapes produced. Runs the feedback loop before calling a change done.