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/BrennanJCollins/UnabatedPM-coachingWrote 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/brennanjcollins/unabatedpm-coaching/coach-job-search)<a href="https://agentmods.dev/commands/brennanjcollins/unabatedpm-coaching/coach-job-search"><img src="https://agentmods.dev/badge/commands/brennanjcollins/unabatedpm-coaching/coach-job-search/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/brennanjcollins/unabatedpm-coaching/coach-job-search"><img src="https://agentmods.dev/badge/commands/brennanjcollins/unabatedpm-coaching/coach-job-search.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 | $0.00037 | $0.00903 |
| Opus 5 | $0.00018 | $0.00451 |
| Sonnet 5 | $0.00007 | $0.00181 |
| Haiku 4.5 | $0.00004 | $0.00090 |
Grade A, and why
Coach Job Search 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 12d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are guiding me through a complete job search preparation workflow using three coaching frameworks from The Influential PM course by Brennan Collins. Work through each step in sequence, completing one before moving to the next.
Here is my job search context:
[Paste your context here: your current role and experience, target role/companies, your resume (full text or key sections), what's working and what isn't in your search, and any specific interviews coming up.]
Step 1: Resume as Product Design
Start by coaching me to treat my resume as a product with a conversion funnel:
- Summary/Headline: Does it create intrigue or read like a biography?
- Experience Bullets: Do they tell strategic stories (Situation → Challenge → Approach → Outcome) or list tasks?
- Niche Signal: Can you tell what KIND of PM I am, or could this resume belong to anyone?
Catch the red flags: "Managed," "Coordinated," "Led" without outcomes, "Cross-functional collaboration" without specifics, and any bullet that describes what I DID instead of what I DECIDED.
Rate my resume: Biography (lists attributes) / Functional (describes role type) / Intriguing (makes them want to read more)
Provide: A rewritten summary, 3 rewritten bullets, and a language audit showing delivery-language words and their strategic replacements.
When the resume is at Functional or Intriguing level, move to Step 2.
Step 2: Niche Job Search Strategy
Now coach me to narrow my search using the Product-Launch Job Search Framework:
- Define My ICP: What type of company (stage, industry, culture) is the best fit for my specific strengths?
- Narrow My Messaging: Am I competing against everybody, or have I chosen a niche?
- Build a Target List: 15-20 companies that match my ICP, not 200 random applications
- Warm Referral Strategy: For each target, how do I get a warm introduction instead of a cold application?
Apply the key test: "You actually want fewer interviews. And fewer responses, because you've chosen a niche with your language."
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.
- 12d ago First seen · 76 lines · 37 tokens per session scan A 4bda6b6f0a47
Coach Job Search is a command published in the GitHub repository BrennanJCollins/UnabatedPM-coaching (4 stars, last pushed 22d ago), licensed MIT. It adds 37 tokens to every session and 903 once invoked, about $0.0002 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
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ship-a-feature
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rescue-an-account
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setup-context
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focus-report
One-screen focus snapshot — avg turn duration, thinking-block usage, and longest sessions.