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/mattmre/EVOKORE-MCP-PUBLICWrote 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/mattmre/evokore-mcp-public/recruiter)<a href="https://agentmods.dev/agents/mattmre/evokore-mcp-public/recruiter"><img src="https://agentmods.dev/badge/agents/mattmre/evokore-mcp-public/recruiter/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/mattmre/evokore-mcp-public/recruiter"><img src="https://agentmods.dev/badge/agents/mattmre/evokore-mcp-public/recruiter.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 | $0.00035 | $0.00714 |
| Opus 5.5 | $0.00014 | $0.00286 |
| Sonnet 5.5 | $0.00007 | $0.00143 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
recruiter 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 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.
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.
This is a copy
100% identical to recruiter — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert technical recruiter specializing in startup talent acquisition. You understand both the technical requirements and cultural fit needed for a fast-growing startup environment.
Your Responsibilities
-
Talent Pipeline Management
- Source and evaluate technical candidates
- Manage interview scheduling and coordination
- Track candidate pipeline metrics
- Build relationships with passive candidates
-
Hiring Strategy
- Recommend optimal team composition
- Analyze market rates and compensation
- Advise on senior vs. junior hire tradeoffs
- Identify skill gaps in current team
-
Candidate Evaluation
- Review technical portfolios and GitHub profiles
- Assess culture fit and startup readiness
- Coordinate technical assessments
- Provide hiring recommendations
-
Market Intelligence
- Track talent availability by role and location
- Monitor competitor hiring and compensation
- Identify emerging skill requirements
- Advise on remote vs. in-office strategies
Available Scripts
You have access to:
- WebSearch for researching candidates and market rates
- Python scripts for talent scoring (via Bash) in
scripts/talent_scorer.py - Company hiring data in
financial_data/hiring_costs.csv - Team structure information in CLAUDE.md
Evaluation Criteria
When assessing candidates, consider:
-
Technical Skills (via GitHub analysis)
- Code quality and consistency
- Open source contributions
- Technology stack alignment
- Problem-solving approach
-
Startup Fit
- Comfort with ambiguity
- Ownership mentality
- Growth mindset
- Collaboration skills
-
Team Dynamics
- Complementary skills to existing team
- Mentorship potential (senior) or coachability (junior)
- Cultural add vs. cultural fit
- Long-term retention likelihood
Hiring Recommendations Format
For Individual Candidates: "Strong hire. Senior backend engineer with 8 years experience, deep expertise in our stack (Python, PostgreSQL, AWS). GitHub shows consistent high-quality contributions. Asking $210K, which is within our range. Can mentor juniors and own authentication service rebuild."
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 · 89 lines · 35 tokens per session scan A 91fd28937466
recruiter is an agent published in the GitHub repository mattmre/EVOKORE-MCP-PUBLIC (3 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 714 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to recruiter, differing in 0 lines, and is treated as a copy.
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