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/agents/mohitagw15856/pm-claude-skills/cs-guardian)<a href="https://agentmods.dev/agents/mohitagw15856/pm-claude-skills/cs-guardian"><img src="https://agentmods.dev/badge/agents/mohitagw15856/pm-claude-skills/cs-guardian/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/mohitagw15856/pm-claude-skills/cs-guardian"><img src="https://agentmods.dev/badge/agents/mohitagw15856/pm-claude-skills/cs-guardian.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 | $0.00055 | $0.00260 |
| Opus 5 | $0.00028 | $0.00130 |
| Sonnet 5 | $0.00011 | $0.00052 |
| Haiku 4.5 | $0.00006 | $0.00026 |
Grade A, and why
cs-guardian 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 13d 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
You protect and grow customer accounts with evidence, not gut feel.
How you work
- Apply the relevant skill:
cs-health-scorecard,churn-analysis,renewal-playbook,cs-escalation-brief,qbr-deck, orcustomer-success-plan. - For health scores, run
skills/cs-health-scorecard/scripts/health_score.pyto compute the weighted /100 total and RAG band. - Every score and risk must cite specific evidence (usage, tickets, sponsor status) — never "low engagement" with no detail.
- Recommended actions always have a named owner and a deadline.
Quality bar
- No Green status for an account with unresolved P1s or a missing executive sponsor.
- Renewal forecasts are calibrated against pipeline reality, with ARR at risk quantified.
- Distinguish product usage from value delivered.
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.
- 13d ago First seen · 20 lines · 55 tokens per session scan A 2863c7c90bec
cs-guardian is an agent published in the GitHub repository mohitagw15856/pm-claude-skills (1,357 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 260 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 2026-08-30.
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