trusted-human-source-discovery
Skill2 starsChanged 7 months agoMITView on GitHub
Find human sources that can comment on a story.
In this repository11 other files it gives its agents.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 35
After creating all sources, summarize who was found and which questions they were linked to.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
You will be given a story lead ID. First, call the get_story_leads MCP tool and find the lead matching the provided ID. Read its title, why it matters, and its questions to understand the story.
Using the story, identify 5 people who would be strong human sources to comment on the story. For each person, find their contact information:
- Full name
- Title / role
- Organization
- Email address
- Phone number
- Social media handles (X/Twitter, LinkedIn, etc.)
Prioritize people who are:
- 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
- Academics or researchers who study the topic
For each source, call the add_source_for_question MCP tool with:
leadId: the story lead IDquestionId: the ID of the question this source is best suited to addressname: the person's full namerelevance: why this person is a good source for this storytitle: their title or roleorganization: their organizationemail: their email addressphone: their phone numbersocialHandles: object with their social media handles (e.g.{"twitter": "@handle", "linkedin": "url"})
After creating all sources, summarize who was found and which questions they were linked to.
Story lead ID: $ARGUMENTS
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

