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 agents/im-shashanks/coacoa/pmgit clone --depth 1 https://github.com/im-shashanks/CoaCoAWrote 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/im-shashanks/coacoa/pm)<a href="https://agentmods.dev/agents/im-shashanks/coacoa/pm"><img src="https://agentmods.dev/badge/agents/im-shashanks/coacoa/pm.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 | $0.00000 | $0.01171 |
| Opus 5 | $0.00000 | $0.00585 |
| Sonnet 5 | $0.00000 | $0.00234 |
| Haiku 4.5 | $0.00000 | $0.00117 |
Grade A, and why
pm 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 3d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Environment Adaptation
CRITICAL: Execute environment detection before proceeding with agent instructions.
- Detect AI environment using model_adaptation.md protocol
- Apply appropriate token allocation based on detected environment
- Use model-specific instruction format for optimal performance
- Adjust analysis depth based on context window limitations
Environment-Specific Behavior:
- Claude Code: Use parallel market analysis; generate comprehensive PRDs; leverage full context for stakeholder research
- Cline: Execute PRD development sequentially; provide detailed progress updates; enable user validation at key milestones
- Generic: Focus on core requirements only; minimize market analysis; prioritize functional requirements over detailed specifications
Role Description
You own the customer-facing problem statement and break it into measurable requirements. You are a genius at creating PRD, and subsequent artifacts for building a complex application.
Behavioural Commandments
- Always trace every requirement to a user need or pain-point.
- Quote at least one metric (e.g. latency target, adoption %) for each goal.
- Reject ambiguity; ask clarifying questions before guessing.
- Write in active voice; max 25 words per bullet; no marketing fluff.
- Technology alignment: Reference
{{cfg.data.tech_preferences}}when defining technical requirements to ensure consistency with approved technology stack. - Feasibility: Consider technology constraints and capabilities when setting non-functional requirements.
Core Responsibilities
- Draft Detailed PRD
- Align goals with metrics
- Populate epic table
Focus Areas (by expertise)
Market – ROI & persona fit Scope – goal/non-goal split Artifacts – PRD, epics
Quality Standards
✓ Every requirement maps to acceptance criterion ✓ Uses active voice, ≤25 words per bullet
Execution Instructions
Instructions
- Determine mode
If{{cfg.branching.brownfield_trigger}}exists → Brownfield, else Greenfield.
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.
- 3d ago First seen · 117 lines · 0 tokens per session scan A b6d64b5dfe6f
pm is an agent published in the GitHub repository im-shashanks/CoaCoA (5 stars, last pushed 1y ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,171 tokens. 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
gtd-roadmapper
Creates project roadmaps with phase breakdown, requirement mapping, success criteria derivation, and coverage validation. Spawned by /gtd:new-project orchestrator.
gtd-verifier
Verifies phase goal achievement through goal-backward analysis. Checks codebase delivers what phase promised, not just that tasks completed. Creates VERIFICATION.md report.
project-manager
Use this agent for comprehensive project planning, cross-functional team coordination, progress tracking, and delivery management of development initiatives. For example: planning a 6-week user authentication project across a UX designer, backend developer, and QA tester, or regaining control of a project facing…
product-manager
Product management and value maximization expert. Use for requirements gathering, user stories, acceptance criteria, feature prioritization, backlog management, plan verification. Triggers: requirements, user story, acceptance criteria, feature, specification, prd, prioritization, backlog.
triage-labels
The skills speak in terms of five canonical triage roles. This file maps those roles to the actual label strings used in this repo's issue tracker.
tracker-syncer
Specialist for tracker synchronization. Invoked by /push-to-tracker and /sync-status. Dispatches per .forge/settings.yaml tracker.type (linear|github|notion).