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/fabriqaai/specs.md/fire-plannergit clone --depth 1 https://github.com/fabriqaai/specs.mdWrote 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/fabriqaai/specs.md/fire-planner)<a href="https://agentmods.dev/commands/fabriqaai/specs.md/fire-planner"><img src="https://agentmods.dev/badge/commands/fabriqaai/specs.md/fire-planner.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 | $0.00013 | $0.00319 |
| Opus 5 | $0.00006 | $0.00160 |
| Sonnet 5 | $0.00003 | $0.00064 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
fire-planner 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.
What it actually says
Activate FIRE Planner
Command: /specsmd-fire-planner
Activation
You are now the FIRE Planner Agent for specsmd.
IMMEDIATELY read and adopt the persona from:
→ .specsmd/fire/agents/planner/agent.md
Critical First Steps
- Read Config:
.specsmd/fire/memory-bank.yaml - Read State:
.specs-fire/state.yaml - Determine Mode:
- No active intent →
intent-captureskill - Intent without work items →
work-item-decomposeskill - High-complexity work item →
design-doc-generateskill
- No active intent →
Your Skills
- Intent Capture:
.specsmd/fire/agents/planner/skills/intent-capture/SKILL.md→ Capture new intent - Work Item Decompose:
.specsmd/fire/agents/planner/skills/work-item-decompose/SKILL.md→ Break into work items - Design Doc Generate:
.specsmd/fire/agents/planner/skills/design-doc-generate/SKILL.md→ Create design doc
Routing Targets
- Back to Orchestrator:
/specsmd-fire - To Builder:
/specsmd-fire-builder
Begin
Activate now. Read your agent definition and start planning.
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 · 49 lines · 13 tokens per session scan A 45c6e4b84ad9
fire-planner is a command published in the GitHub repository fabriqaai/specs.md (205 stars, last pushed 12d ago), licensed MIT. It adds 13 tokens to every session and 319 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 2026-08-30.
Other commands, from other repositories
taskstoissues
Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.
Issue Spec: Apply
Implement directly or use an optional PROCESS when managed coordination is required.
/spdd-story
Decompose high-level feature requirements into INVEST-compliant, business-focused stories with clear scope boundaries and testable acceptance criteria.
pm-setup
비개발자 PM 이 새 프로젝트에서 Claude Code 를 처음 쓸 때, 제품·타깃·메트릭을 소크라틱 인터뷰로 물어 CLAUDE.md 8축 초안 + INDEX.md 지식 지도 초안을 자동 작성 한다. 한 번의 대화로 "AI 가 우리 제품을 안다" 상태를 만드는 것이 목적이다.
start-3
PM 의 핵심 흐름인 Discovery → Definition → Delivery 를 작은 가상 과제 하나로 끝까지 관통한다. 각 단계에서 실제 챕터를 읽고, 직접 산출물 한 조각을 만들어 다음 단계로 넘긴다.
briefing
연결된 도구(Slack / Linear / Notion / GitHub / 캘린더)에서 어제오늘의 신호를 모아 PM 의 오늘 우선순위 5개 로 압축 출력한다.