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.
npx agentmods add commands/dcassil/resume-kit/setupgit clone --depth 1 https://github.com/dcassil/resume-kitWhat 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 | $0.00017 | $0.00334 |
| Opus 5 | $0.00009 | $0.00167 |
| Sonnet 5 | $0.00003 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00033 |
Grade A, and why
setup 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 yesterday.
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.
What it actually says
Install the resume-kit package so this plugin's MCP server (resume-kit-mcp)
and the resume-tool CLI are available.
Prefer uv when it is present; otherwise fall back to pip. Run:
uv tool install "resume-kit[all]"
If uv is not installed, use pip instead:
pip install "resume-kit[all]"
Then confirm the command now exists:
resume-kit-mcp --help >/dev/null 2>&1 && echo "resume-kit installed OK"
On success, tell the user to run /reload-plugins (or restart Claude Code) so
the resume-kit MCP server starts and its tools become available.
If installation fails, show the error output and suggest checking that Python
and uv/pip are available and that PyPI is reachable.
Deterministic extraction is included in the base install
The base resume-kit[all] install already bundles markitdown, pdfminer.six,
and python-docx. The resume-tool extract --no-llm <file> CLI can extract
text from PDF, DOCX, Markdown, and plain-text files without any optional extras.
Use this as the primary extraction path in the parse-resume and
parse-job skills.
The markitdown[pdf] optional extra is not required for extraction and does not
need to be installed as part of normal setup.
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.
- yesterday First seen · 42 lines · 17 tokens per session scan A 02dc9cd6920f
setup is a command published in the GitHub repository dcassil/resume-kit (0 stars, last pushed 21d ago), licensed Apache-2.0. It adds 17 tokens to every session and 334 once invoked, about $0.0001 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
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.