present-candidates
Skill2 starsChanged 6 months agoApache-2.0View on GitHub
Analyze sub-directions within the user's chosen field and present ranked candidates. Combines sub-direction identification, skill-gap matching, and presentation into a single SOP. Depth scales by start mode: cold-start shows broad sub-directions, warm-start shows specific sub-problems, hot-start shows granular technical details.
In this repository32 other files it gives its agents.
- actor-profilingSkill
- and-or-decomposeSkill
- ask-constraintsSkill
- ask-decomposition-validationSkill
- ask-intentionalitySkill
- ask-obstacle-acceptanceSkill
- assess-obstacle-severitySkill
- broad-paper-searchSkill
- broad-web-searchSkill
- clarify-resourcesSkill
- cold-startSkill
- crystallize-north-starSkill
- deep-web-searchSkill
- direction-narrowingSkill
- explore-resumeSkill
- feasibility-checkSkill
- final-validationSkill
- formulate-top-goalSkill
- generate-candidate-fieldsSkill
- generate-research-briefSkill
- goal-decompositionSkill
- hot-startSkill
- identify-obstaclesSkill
- landscape-reconnaissanceSkill
- landscape-synthesisSkill
- north-star-crystallizationSkill
- north-star-synthesisSkill
- obstacle-analysisSkill
- present-and-askSkill
- propose-mitigationsSkill
- validate-leavesSkill
- warm-startSkill
The file
Files
Present Candidates
Analyze + present sub-directions as ranked candidates.
Execution
Dialogue — inline, CC does the analysis and presents directly.
What to Do
- From broad-paper-search and deep-web-search results, identify distinct sub-directions within the chosen field
- For each sub-direction, assess: current activity level, gap size, skill fit with ActorProfile
- Rank and present to user
Depth Scales by Start Mode
- cold-start: "Here are the broad sub-directions you could pursue in [field]"
- warm-start: "Within [direction], here are the specific sub-problems and research tracks"
- hot-start: "For [specific topic], here are the granular knowledge points and technical details to consider"
What to Ask (one at a time)
- Which of these excites you most?
- Where do you think you could make a unique contribution?
Output
RankedCandidates[] + user's selection.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
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.