Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add archugunov/pm-job-search/plugin install pm-job-searchWrote 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/skills/archugunov/pm-job-search/evaluate-offer)<a href="https://agentmods.dev/skills/archugunov/pm-job-search/evaluate-offer"><img src="https://agentmods.dev/badge/skills/archugunov/pm-job-search/evaluate-offer/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/skills/archugunov/pm-job-search/evaluate-offer"><img src="https://agentmods.dev/badge/skills/archugunov/pm-job-search/evaluate-offer.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 | $0.00197 | $0.03846 |
| Opus 5 | $0.00098 | $0.01923 |
| Sonnet 5 | $0.00039 | $0.00769 |
| Haiku 4.5 | $0.00020 | $0.00385 |
Grade A, and why
evaluate-offer 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 11d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/evaluate-offer — sense-check an offer against your bigger plan
A senior-PM-tuned offer evaluation. Reads the user's profile + strategy + company history, applies the senior-PM-archetype + anti-pattern references, and produces a verdict with specific negotiation moves. Different from /evaluate-position — that scores opportunities (postings) against your tier rubric; this scores offers in hand against your career arc.
Voice: every prompt and the written evaluation follows ${CLAUDE_PLUGIN_ROOT}/TONE.md. Apply the low-effort-first principle — ask for the smallest set of offer details that unlocks a useful verdict; only drill if a load-bearing detail is missing.
Inputs
- Offer details — collected conversationally. Required minimum:
- Company name
- Title
- Base salary + currency
- Equity (% or $ value, vesting + cliff if known)
- Sign-on (if any)
- Stage (seed / Series A / B / C / D+ / late-stage / public)
- Location / remote arrangement
- Manager (name + brief)
- Start date (if discussed)
- User-provided fit notes (e.g. "their CPO is on parental leave for the first 4 months")
- Second offer (optional) — if the user mentions a second offer or
--compare-with <Company>, collect the same minimum set for the second offer and produce a side-by-side comparison instead of a single-offer verdict. userdata/profile.md— frontmatter (target_titles,salary_band,geography,hard_filters,target_industries),## Positioning,## Moat,## What NOT to Frame As.userdata/strategy.md— frontmatter (target_offer_date,weekly_targets),## Headline goal,## Anti-goals,## Checkpoints.userdata/companies/<Company>/[<role-slug>/]meta.md+research-brief.md+ any priorinterview-debrief-*.mdif the company is in the pipeline. Especially: the most recent debrief's "role shape verdict" (🟢 / 🟡 / 🔴) is load-bearing for this evaluation.- Reference docs (per TONE.md userdata-override convention):
userdata/references/senior-pm-archetypes.md||${CLAUDE_PLUGIN_ROOT}/references/senior-pm-archetypes.md— used for archetype-fit diagnosis (does the role need a builder / scaler / operator? does your positioning match?).userdata/references/career-anti-patterns.md||${CLAUDE_PLUGIN_ROOT}/references/career-anti-patterns.md— used to scan for #2 title-chasing, #3 stage-mismatch, #9 hollow-HoP, #10 comp-tunnel-vision. Surface BY NAME when detected.
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.
- 11d ago First seen · 212 lines · 0 tokens per session scan A 83df7acca3d1
evaluate-offer is a skill published in the GitHub repository archugunov/pm-job-search (7 stars, last pushed 16d ago), licensed MIT. It adds 197 tokens to every session and 3,846 once invoked, about $0.0010 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.
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