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/dtannen/pm/initgit clone --depth 1 https://github.com/dtannen/pmWhat 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 | $0.00011 | $0.03077 |
| Opus 5 | $0.00005 | $0.01538 |
| Sonnet 5 | $0.00002 | $0.00615 |
| Haiku 4.5 | $0.00001 | $0.00308 |
Grade A, and why
init 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 yesterday.
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 — 474 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Initialize PM Adaptive Workflow
Initialize the PM Adaptive Workflow system with intelligent complexity assessment and mode selection.
Usage
/pm:init
Instructions
You are initializing the PM Adaptive Workflow - a intelligent system that automatically scales complexity handling based on task needs.
MCP Integration (optional)
Optionally seed an MCP project/epic context for tracking initialization work and future tasks.
- Full name: mcp__project-manager-mcp__create_task — Seed a project/epic by creating a setup task
- Full name: mcp__project-manager-mcp__update_task — Append logs and RA metadata
- Full name: mcp__project-manager-mcp__get_instructions — Retrieve methodology text for RA references
Suggested flow:
- Create a setup task:
mcp__project-manager-mcp__create_task(name="Initialize PM Adaptive Workflow", project_name="{YourProject}", epic_name="Project Setup", ra_mode="standard", ra_score="4"). - Attach initialization outputs (paths created, templates written) to
ra_metadata.initviamcp__project-manager-mcp__update_taskwith alog_entry. - Store RA methodology reference snippet from
mcp__project-manager-mcp__get_instructions(optional) inra_metadata.references.
1. Create Project Structure
Create the following directories:
.pm/
├── prds/ # Product Requirements Documents
├── epics/ # Technical implementation plans
├── tasks/ # Granular task breakdowns
├── patterns/ # Learned patterns and assessments
└── config.json # Adaptive configuration
2. Create Configuration File
Create .pm/config.json:
{
"workflow_mode": "adaptive",
"auto_assess": true,
"complexity_thresholds": {
"simple": 3,
"standard": 6,
"ra_light": 8,
"ra_full": 10
},
"mode_overrides": {},
"learning_enabled": true,
"parallel_execution": true,
"github_sync": true,
"project_started": "{timestamp}",
"metrics": {
"tasks_completed": 0,
"average_complexity": 0,
"assumption_accuracy": null
}
}
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.
- yesterday First seen · 474 lines · 11 tokens per session scan A e1c88b524e9e
init is a command published in the GitHub repository dtannen/pm (0 stars, last pushed 10mo ago), licensed MIT. It adds 11 tokens to every session and 3,077 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
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.