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/analyze-job-fit/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/analyze-job-fit)<a href="https://agentmods.dev/skills/farrelfatah/nextjobkit/analyze-job-fit"><img src="https://agentmods.dev/badge/skills/farrelfatah/nextjobkit/analyze-job-fit/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/analyze-job-fit"><img src="https://agentmods.dev/badge/skills/farrelfatah/nextjobkit/analyze-job-fit.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 | $0.00056 | $0.00554 |
| Opus 5 | $0.00028 | $0.00277 |
| Sonnet 5 | $0.00011 | $0.00111 |
| Haiku 4.5 | $0.00006 | $0.00055 |
Grade A, and why
analyze-job-fit 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Job Fit
Turn a job listing into an evidence-backed application decision.
Gather the Real Job Surface
- Read
profile/candidate.mdand resolve the configured master and evidence files. - Inspect the complete current listing or supplied job description. If no live source or publication date is available, label listing currency as unverified.
- When preparing an application, inspect the live form and later screening steps when authorized and accessible.
- Distinguish required qualifications, preferred qualifications, responsibilities, outcomes, logistics, and legal eligibility.
- Record the source and date. Mark anything inferred from the listing as an inference.
Build the Requirement Map
Use this structure:
| Requirement | Priority | Confirmed evidence | Gap or risk | Application treatment |
|---|
For every important requirement:
- Cite specific candidate evidence.
- Mark adjacent evidence as adjacent, not direct.
- Keep missing evidence visibly missing.
- Separate hard gates from trainable gaps.
Do not calculate a match percentage. The inputs are too subjective for the precision to mean anything.
Make a Decision
Choose one recommendation:
Pursue: strong evidence and no known hard gate.Pursue with caveats: credible fit with explicit gaps or eligibility uncertainty.Low priority: possible fit but weak evidence or poor strategic alignment.Do not pursue: a confirmed hard gate or material mismatch makes the application wasteful.
Explain the decisive factors, not every keyword in the listing.
Produce a Tailoring Brief
Identify:
- The role's actual hiring thesis.
- Three to five evidence clusters to foreground.
- Claims and keywords that are supported.
- Claims that must not be made.
- Evidence questions that block responsible tailoring.
- Relevant portfolio projects and likely interview risks.
When the user has requested application preparation, add a dated target-job note to the evidence file. In read-only analysis or evaluation, return the proposed note without editing. Do not alter the master or create a tailored resume unless requested.
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.
- 11d ago First seen · 66 lines · 56 tokens per session scan A 0fb25a7830e8
analyze-job-fit is a skill published in the GitHub repository farrelfatah/nextjobkit (5 stars, last pushed 21d ago), licensed MIT. It adds 56 tokens to every session and 554 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 2026-08-31.
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