Borrowing it
Nothing to install: this file belongs to farrelfatah/nextjobkit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/farrelfatah/nextjobkit/main/.agents/skills/discover-resume-evidence/SKILL.mdgit clone --depth 1 https://github.com/farrelfatah/nextjobkitWrote 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/farrelfatah/nextjobkit/discover-resume-evidence)<a href="https://agentmods.dev/skills/farrelfatah/nextjobkit/discover-resume-evidence"><img src="https://agentmods.dev/badge/skills/farrelfatah/nextjobkit/discover-resume-evidence/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/farrelfatah/nextjobkit/discover-resume-evidence"><img src="https://agentmods.dev/badge/skills/farrelfatah/nextjobkit/discover-resume-evidence.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 | $0.00062 | $0.00531 |
| Opus 5.5 | $0.00025 | $0.00212 |
| Sonnet 5.5 | $0.00012 | $0.00106 |
| Haiku 4.5 | $0.00006 | $0.00053 |
Grade A, and why
discover-resume-evidence 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 2mo 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discover Resume Evidence
Build proof before polishing prose.
Start With the Sources
- Read
profile/candidate.md. - Resolve and read the configured evidence file and master resume.
- Inspect relevant portfolio, application, or project artifacts when available.
- Separate what is confirmed from what merely sounds plausible.
Interview Method
Ask five to seven high-impact questions per round. Prioritize gaps that could change positioning, placement, dates, ownership, or outcomes.
Ask for:
- The candidate's personal contribution.
- The artifact or deliverable created.
- Users, customers, stakeholders, or systems affected.
- The problem, constraint, and decision.
- Verifiable scale or outcome.
- Dates, title, organization, and team.
- Links, screenshots, documents, repositories, or testimonials.
After each round:
- Summarize confirmed facts.
- Extract resume-ready evidence without embellishment.
- Mark assumptions and unresolved questions.
- Update the configured evidence file.
- Ask another round only when remaining gaps materially affect the result.
Evidence States
Use explicit states:
Confirmed: directly supplied or verified.Partially confirmed: core fact is supported but important details remain.Needs confirmation: not safe to use in a final artifact.Excluded: true but irrelevant, private, misleading, or narratively weak.
Treat unlisted work as a candidate entry. Record its type, organization, dates, confidence, possible placement, and remaining questions before adding it to the master resume.
Metric Rules
Use this order:
Measured fact > user-confirmed conservative estimate > concrete qualitative evidence > omission
Never reverse-engineer an impressive number from a hunch. If a calculation uses confirmed inputs, show the calculation in evidence notes and ask the user to approve the resulting claim.
Boundaries
- Do not rewrite the resume unless the user also asks for a rewrite.
- Do not force every bullet to contain a number.
- Do not convert team results into personal ownership without proof.
- Do not expose private application answers unnecessarily.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 70 lines · 62 tokens per session scan A 8de1dd945282
discover-resume-evidence is a skill published in the GitHub repository farrelfatah/nextjobkit (5 stars, last pushed 16d ago), licensed MIT. It adds 62 tokens to every session and 531 once invoked, about $0.0002 per session on Opus 5.5. 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.
discover-resume-evidence compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| discover-resume-evidencefarrelfatah/nextjobkit | Skill | 5 | 16d ago | MIT | A | 62 | Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |