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 cxcscmu/SkillLearnBench --skill json-extractiongit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/json-extraction)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/json-extraction"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/json-extraction.svg" alt="Measured on agentmods" 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 | $0.00021 | $0.00335 |
| Opus 5 | $0.00010 | $0.00168 |
| Sonnet 5 | $0.00004 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
json-extraction 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 3d 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.
What it actually says
JSON Extraction Skill
This skill covers how to efficiently navigate and extract information from the enterprise data JSON files.
Data Structure
The product data files (e.g., /root/DATA/products/Product.json) typically have the following structure:
slack: A list of channel messages. Each message has aUser,text, andtimestamp.documents: A list of document metadata, includingauthor,date,type, andcontent.meeting_transcripts: Transcripts of meetings.urls: Shared URLs and their descriptions.
Techniques
Extracting Document Authors and Reviewers
- Search the
documentslist for a specifictype(e.g., "Market Research Report"). - Identify the
authorfield. - Search
slackmessages around the document'sdateto find discussions and feedback. - Users who provide specific suggestions or critiques in the Slack threads are considered reviewers.
Identifying Competitor Insights
- Search
slackmessages andmeeting_transcriptsfor keywords like "competitor", "strengths", "weaknesses", or specific competitor names (e.g., "Salesforce", "HubSpot"). - Map the
userIdfrom those messages to identify the team members.
Finding Shared URLs
- Search the
slackmessages for "http" or "demo". - Cross-reference with the
urlslist in the JSON if available.
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.
- 3d ago First seen · 31 lines · 21 tokens per session scan A aab33677697b
json-extraction is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 335 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 2026-09-03.
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