jd-intel AGENTS.md

Repository instructions for `jd-intel`, an open-source library, command-line tool, and MCP server that makes job descriptions easier for AI systems to use. They also define privacy rules for keeping personal, employer, applicant, and internal details anonymous.

In plain words
What is it for?
Use them when developing or documenting `jd-intel`, its npm packages, CLI, or MCP server, especially when handling job descriptions, public technical artifacts, or author-related details.
Why use it?
They help contributors understand the project’s purpose and avoid exposing private or identifying information in its public code and documentation.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/prpmdev/jd-intel/agents-md
Clone the repo
git clone --depth 1 https://github.com/prPMDev/jd-intel

Made for: Codex, OpenCode.

Per session 3,480 This file is loaded in full into every session.
When invoked 3,480 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.03480 $0.03480
Opus 5 $0.01740 $0.01740
Sonnet 5 $0.00696 $0.00696
Haiku 4.5 $0.00348 $0.00348

Measured yesterday against content hash 201f9cca191e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

jd-intel AGENTS.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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

AGENTS.md · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 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.

Read the full file on GitHub · 260 lines

Changes

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.

  1. yesterday First seen · 260 lines · 3,480 tokens per session scan A 201f9cca191e

Subscribe to this mod's changes

jd-intel AGENTS.md is an instructions file published in the GitHub repository prPMDev/jd-intel (2 stars, last pushed 8d ago), licensed MIT. It adds 3,480 tokens to every session, about $0.0174 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.