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fuse

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UpdatedJuly 9, 2026 at 15:24

Combine two AI agent skills into one. Trigger phrases: /fuse, "fuse these skills", "combine skills", "merge these two skills", "create a fusion skill"

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gaia-research

gaia-research/gaia-skill-tree

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SKILL.md

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name	fuse
description	Combine two AI agent skills into one. Trigger phrases: /fuse, "fuse these skills", "combine skills", "merge these two skills", "create a fusion skill"

A sequential routing pipeline to compose two installed skills into a single integrated agent capability.

Setup

Check for the existence of .agents/skills/, .claude/skills/, or .cursor/rules/ to locate the target skills directory.
Note if a .gaia/ directory is present in the workspace root.

Routing Table

Execute these steps in order to perform a skill fusion:

Step	Action	Reference
1	Detect -- find and confirm the two source skills	reference/detect.md
2	Compose -- read sources and apply the fusion prompt	reference/compose.md
3	Name -- propose, validate, and select a target name	reference/name.md
4	Register -- write the files and log the fusion event	reference/register.md

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Consult this skill BEFORE proposing a fix to any CLI gap or schema gap that touches evidence, trust magnitude, evidence types, evidence grades, the TM formula, or star-level promotion gates. Also read it whenever an issue mentions citations, stars, commits, contributors, views, reviewers, percentile, arxiv, github-stars-own, repo-own, social-signal, benchmark-result, peer-review, self-attestation, fusion-recipe, verifier-attestation, or proxy-containment — those are the 10 canonical evidence types and the raw inputs that feed their formulas. Also read it when asked whether a skill qualifies for a given star level (0★–6★): the Star Bar and promotion gates live in `META.md`, not in the TM methodology page. Reading both prevents proposing a calibration that satisfies the TM grade threshold but violates a Star Bar installability or link requirement.

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gaia-research/gaia-skill-tree

Phase 4 of the Gaia evidence verification pipeline. Checks every URL in the evidence data lake for HTTP liveness — catches dead links (404, 403, timeout, connection errors) before evidence is ingested into the registry. Use this skill when: running the full /ev-pipeline, asked to "validate links", "check evidence URLs", "run link validation", "find dead links in the data lake", "check HTTP status of evidence sources", or "verify evidence links still work". Also useful standalone when you suspect evidence sources have gone stale after a long gap between pipeline runs. Wraps validate_sources.py, which uses Firecrawl CLI to scrape each unique URL and records pass/fail status in a markdown report. Requires Firecrawl CLI to be installed and authenticated.

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gaia-research/gaia-skill-tree

Top-level orchestrator for the Gaia Registry evidence verification pipeline. Run this when you want to do a full evidence pass — collecting raw sources, verifying live GitHub star counts, adversarially auditing for quality/formatting issues, and checking that every URL is reachable — all in one coordinated sequence. Trigger phrases: "run the evidence pipeline", "full evidence pass", "verify evidence", "evidence verification pipeline", "run ev-pipeline", "check all evidence", "audit the data lake", "evidence quality sweep", "refresh evidence", "validate evidence sources". Also aliased as /evidence-verification-pipeline. Use the individual sub-skills (ev-collection, ev-star-verification, ev-adversarial-audit, ev-link-validation) only when you need to re-run one phase in isolation; for end-to-end work, always start here.

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gaia-research/gaia-skill-tree

Canonical entry point for the full Gaia evidence verification pipeline. Invoke as /evidence-verification-pipeline or /ev-pipeline — both names trigger this skill. Use whenever you need to run all four evidence phases end-to-end: collecting raw evidence from the data lake, verifying live GitHub star counts, running adversarial auditing for noise and URL errors, and checking link health via Firecrawl. Also use when someone says "run the evidence pipeline", "verify the evidence lake", "audit evidence", "run ev-pipeline", "full evidence check", "pipeline run", "prepare evidence for ingestion", or "refresh the data lake". This is the pre-ingestion step — run it before importing any evidence into the registry.

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name	fuse
description	Combine two AI agent skills into one. Trigger phrases: /fuse, "fuse these skills", "combine skills", "merge these two skills", "create a fusion skill"

A sequential routing pipeline to compose two installed skills into a single integrated agent capability.

Setup

Check for the existence of .agents/skills/, .claude/skills/, or .cursor/rules/ to locate the target skills directory.
Note if a .gaia/ directory is present in the workspace root.

Routing Table

Execute these steps in order to perform a skill fusion:

Step	Action	Reference
1	Detect -- find and confirm the two source skills	reference/detect.md
2	Compose -- read sources and apply the fusion prompt	reference/compose.md
3	Name -- propose, validate, and select a target name	reference/name.md
4	Register -- write the files and log the fusion event	reference/register.md