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 skills add press-pass/journalism-skills --skill geographic-source-discoverygit clone --depth 1 https://github.com/press-pass/journalism-skillsWrote 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/press-pass/journalism-skills/geographic-source-discovery)<a href="https://agentmods.dev/skills/press-pass/journalism-skills/geographic-source-discovery"><img src="https://agentmods.dev/badge/skills/press-pass/journalism-skills/geographic-source-discovery/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/press-pass/journalism-skills/geographic-source-discovery"><img src="https://agentmods.dev/badge/skills/press-pass/journalism-skills/geographic-source-discovery.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 | $0.00027 | $0.00994 |
| Opus 5 | $0.00014 | $0.00497 |
| Sonnet 5 | $0.00005 | $0.00199 |
| Haiku 4.5 | $0.00003 | $0.00099 |
Grade A, and why
geographic-source-discovery 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
If no zip codes are provided in $ARGUMENTS, tell the user they need to provide at least one zip code (e.g. /journalism-skills:geographic-source-discovery 10001, 10002) and stop.
You are a beat reporter building a source list for a new coverage area. Your job is to find every civic body, government portal, community organization, and informal community channel that publishes information relevant to the provided zip codes.
Phase 1: Map the terrain
For each zip code, research the geographic and civic landscape:
- Identify the area: What neighborhood(s), city, county, and state does this zip code cover?
- Map civic bodies: What government entities have jurisdiction here? Search the web for:
- City/town council or equivalent legislative body
- Community boards or advisory councils
- Local police precinct or sheriff's office
- School district and school board
- Zoning/planning board
- Parks department (local)
- Health department (local)
- Housing authority
- Any special districts (BIDs, land trusts, water districts, etc.)
- Map community organizations: Search for:
- Neighborhood associations and civic groups
- Tenant unions and housing advocacy orgs
- Mutual aid networks
- Religious institutions that serve as community hubs
- Local business associations and chambers of commerce
- Map informal community channels: Search for:
- Facebook groups for the neighborhood (search Facebook for "[neighborhood name] community", "[neighborhood name] residents", etc.)
- Reddit communities (subreddits for the neighborhood, borough, or city)
- Community newsletters or blogs
Write your findings to skills/geographic-source-discovery/skill-output/geographic-source-discovery/<timestamp>/terrain-map.md
in the journalism-skills directory before proceeding to Phase 2. This makes Phase 1 auditable.
Phase 2: Find sources and access methods
For each entity discovered in Phase 1, find its digital presence and the best way to access its information programmatically. For each one:
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 · 88 lines · 27 tokens per session scan A 80ff2901aefe
geographic-source-discovery is a skill published in the GitHub repository press-pass/journalism-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 994 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.
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