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 instructions/prpmdev/jd-intel/claude-mdgit clone --depth 1 https://github.com/prPMDev/jd-intelWhat 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 | $0.03701 | $0.03701 |
| Opus 5 | $0.01851 | $0.01851 |
| Sonnet 5 | $0.00740 | $0.00740 |
| Haiku 4.5 | $0.00370 | $0.00370 |
Grade A, and why
jd-intel CLAUDE.md 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.
This is a copy
92% identical to jd-intel AGENTS.md — 14 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
jd-intel
Toolkit for making job descriptions AI-accessible. Library + CLI + MCP server. Published to npm as jd-intel (lib/CLI) and jd-intel-mcp (MCP server).
Public repo. Open source MIT. Built by Prashant R as a portfolio piece at the intersection of AI, product work, and the integration layer.
PRIME DIRECTIVE: this is a public repo
Anonymity discipline applies throughout, with one explicit exception (author attribution is intentional public credit).
Always anonymize:
- Specific companies the author applied to or considered (use "fintech company", "Company X")
- The author's specific past employers (use "previous employer" or generic role descriptions)
- Names of any testers, reviewers, or collaborators (use "an external reviewer", "a tester")
- Internal feedback, NDA-protected discussions, private commentary
- Visa / immigration details
- Specific salary numbers tied to the author's experience
- Family / personal life details
Allowed (intentional public attribution):
- Author name: Prashant R
- Portfolio: prashantrana.xyz
- LinkedIn: linkedin.com/in/prashant-rana
- npm package names, GitHub repo URLs, public technical artifacts
- Real ATS platform names (Greenhouse, Lever, Ashby) — these are public products
- Generic role types (PM, engineer, designer) — balance, not pile-on
Git history is permanent. Even if you fix it later, old commits remain accessible. Rewriting history is complex and not guaranteed. Better to over-anonymize than expose.
What jd-intel is
A toolkit (three surfaces, one core) for fetching and normalizing job descriptions across major Applicant Tracking Systems:
- Library (
jd-intel) —fetchJobs,searchRegistry,detectAts,applyFilters. ESM, Node 18+. - CLI (
npx jd-intel fetch <slug>) — same capabilities from the terminal. - MCP server (
jd-intel-mcp) — exposes the toolkit to AI assistants via the Model Context Protocol.
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 · 270 lines · 3,701 tokens per session scan A 4d61465972f3
jd-intel CLAUDE.md is an instructions file published in the GitHub repository prPMDev/jd-intel (2 stars, last pushed 9d ago), licensed MIT. It adds 3,701 tokens to every session, about $0.0185 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to jd-intel AGENTS.md, differing in 14 lines, and is treated as a copy.
Other instructions, from other repositories
llm-context.py CLAUDE.md
Instructions for cyberchitta/llm-context.py, covering claude.md, working notes (gitignored) and draining the field notes.
openrouter-mcp-multimodal AGENTS.md
Instructions for stabgan/openrouter-mcp-multimodal, covering agent instructions, before you ship, releasing (read this before publishing), short version and version files (must all match package.json).
seekstone CLAUDE.md
Instructions for shaqmughal/seekstone, covering claude.md, what this repo is, commands, the harness itself (run after npm install) and architecture.
Plonk AGENTS.md
Instructions for ostapondo/Plonk, covering agent rules, layout, adding a module, build & verify and code style.
mcp-dockhand copilot-review.instructions.md
Instructions for strausmann/mcp-dockhand: When reviewing pull requests in this repository.
second-brain AGENTS.md
Instructions for LindaHaviv/second-brain, covering instructions for ai coding agents, what to read first, the rules (non-negotiable), common tasks, the sanctioned way and enforcement, not just instructions.