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 answer-questionsgit 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/answer-questions)<a href="https://agentmods.dev/skills/press-pass/journalism-skills/answer-questions"><img src="https://agentmods.dev/badge/skills/press-pass/journalism-skills/answer-questions/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/answer-questions"><img src="https://agentmods.dev/badge/skills/press-pass/journalism-skills/answer-questions.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 | $0.00522 |
| Opus 5 | $0.00014 | $0.00261 |
| Sonnet 5 | $0.00005 | $0.00104 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
answer-questions 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 9d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use the MCP tools to get all story leads: call get_story_leads.
For each story lead that has questions with status "Pending" or "Approved":
1. Classify each question
Read the question and decide:
- Public info: The answer can be found from government data, news articles, public records, or other web sources.
- Human source needed: The question requires a person's perspective, insider knowledge, or an interview to answer properly.
2. Answer public-info questions
For each question that can be answered with public information:
- Research the answer using web search, browsing official sources, and cross-referencing data.
- Write a concise, factual answer (2-4 sentences) with specific data points when available.
- Save the answer using the
answer_questionMCP tool with:questionId: the question's IDanswerText: the researched answeranswerSourcesJson: array of{"url": "...", "title": "..."}for each source used
Prioritize authoritative sources: government databases, official reports, established news outlets.
3. Identify human sources for interview questions
For each question that requires a human source:
- Identify the best person to answer this question. Consider:
- People directly involved in or affected by the story
- Subject matter experts with relevant credentials
- Public officials or spokespeople with relevant authority
- Advocates or community leaders connected to the topic
- Research their contact information (email, phone, social media).
- Save the human source using the
add_identified_sourceMCP tool with:leadId: the story lead's IDquestionId: the question's ID (so the editor knows which question this source addresses)name,title,organization,email,phone,socialHandlesJson,relevance
- Also save a partial answer using
answer_questionexplaining what is known so far and that a human source has been identified for the full answer.
4. Summarize
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.
- 9d ago First seen · 53 lines · 27 tokens per session scan A 93cf4941aae2
answer-questions 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 522 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…