PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
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/mohitagw15856/pm-claude-skillsWrote 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/mohitagw15856/pm-claude-skills/red-team)<a href="https://agentmods.dev/commands/mohitagw15856/pm-claude-skills/red-team"><img src="https://agentmods.dev/badge/commands/mohitagw15856/pm-claude-skills/red-team/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/commands/mohitagw15856/pm-claude-skills/red-team"><img src="https://agentmods.dev/badge/commands/mohitagw15856/pm-claude-skills/red-team.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 | $0.00023 | $0.00169 |
| Opus 5.5 | $0.00009 | $0.00068 |
| Sonnet 5.5 | $0.00005 | $0.00034 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade B, and why
red-team scanned grade B with 1 finding 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 1mo 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.
Tells the agent never to refusemediumAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
Channel a room of hostile-but-fair expert personas (skeptical CFO, churned customer, staff engineer, competitor, legal/security, the data realist) — each finding a distinct failure mode the author is too close to see. Th Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
What it actually says
Apply the red-team-review skill to pressure-test: $ARGUMENTS
Channel a room of hostile-but-fair expert personas (skeptical CFO, churned customer, staff engineer, competitor, legal/security, the data realist) — each finding a distinct failure mode the author is too close to see. Then rank the most dangerous blind spots by likelihood × impact, write a 12-months-later pre-mortem, and end with the specific, prioritised changes that would most strengthen the plan. Don't just criticise — make it bulletproof. Infer missing detail and label assumptions; never refuse for lack of detail.
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.
- 1mo ago First seen · 9 lines · 23 tokens per session scan B de8365b6a924
red-team is a command published in the GitHub repository mohitagw15856/pm-claude-skills (1,482 stars, last pushed 3d ago), licensed MIT. It adds 23 tokens to every session and 169 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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.
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.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.