How do I install the Harness Similarity skill?

Run npx skillmds@latest add ruvnet/harness-similarity in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Harness Similarity safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Harness Similarity?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Harness Similarity free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Harness Similarity?

ruvnet (@ruvnet) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Harness Similarity by ruvnet — Agent Skill

Name: Harness Similarity
Rating: 4.666666666666667 (3 reviews)
Author: ruvnet

Harness Similarity

ADR-152 — weighted similarity between two harness fingerprints (genome + score JSON). Returns overall score in [0,1] plus per-component breakdown (cosine over 9 numerics, categorical agreement over 4 enums, jaccard over agent_topology). Unblocks ADR-151 §3.2 Recommender, §3.3 Drift Detection, §3.5 Plugin Compat. Pure-TS, no `@metaharness/*` dep — preserves ADR-150's four architectural constraints.

ruvnet Updated Sep 8, 2026

File contents

Surfaces the production similarity function from scripts/_similarity.mjs as a callable skill. Use when an agent needs to:

decide whether to fork an existing harness vs scaffold a new one
rank candidate templates against a target repo's genome
diff two harnesses produced by different teams to find duplicate work
generate the confidence number that ADR-151 §3.2's Recommender wraps

Algorithm (from ADR-152 §Decision)

overall = 0.60·cosine + 0.25·categorical + 0.15·jaccard

cosine — over a 9-dim numerical vector of normalized scorecard + genome dims
categorical — fraction of 4 enum fields that match (repo_type, archetype, template, recommendedMode)
jaccard — |A ∩ B| / |A ∪ B| over the agent_topology[] array

The 3-component design is load-bearing: numerical cosine alone is too coarse (the iter-35 spike showed LEGAL vs DEVOPS at cosine=0.97 despite being unrelated verticals). Categorical + jaccard pull the composite to the correct ordering.

Reference outputs (iter-35 spike fixtures)

Pair	overall	cosine	categorical	jaccard
`LEGAL` × `LEGAL` (self)	1.0000	1.0000	1.0000	1.0000
`LEGAL` × `SUPPORT`	0.8296	0.9987	0.7500	0.2857
`LEGAL` × `DEVOPS`	0.5840	0.9734	0.0000	0.0000

Both invariants from ADR-152 §"Smallest demonstrable spike" hold:

similarity(X, X) === 1 exactly
similarity(LEGAL, DEVOPS) < similarity(LEGAL, SUPPORT) (vertical affinity)

Architectural constraint inheritance (ADR-150)

Removable — pure-TS function, zero static @metaharness/* imports.
Optional — no new dep in package.json.
Graceful — malformed inputs emit { degraded: true, reason } with exit code 2; never throws.
CI-gate — smoke step 17y locks the contract: module exports, spike fixtures reproduce, CLI dispatcher entry registered, MCP tool registered.

Usage

# File inputs
npx ruflo metaharness similarity --a a.json --b b.json

# Memory inputs (records persisted by oia-audit.mjs)
npx ruflo metaharness similarity --a-key harness-X --b-key harness-Y

# Per-dimension breakdown (used by ADR-151 §3.2 Recommender)
npx ruflo metaharness similarity --a a.json --b b.json --per-dimension

# Alert when too-dissimilar (used by ADR-151 §3.3 Drift Detection)
npx ruflo metaharness similarity --a a.json --b b.json --alert-below 0.5

Implementation

Production module: scripts/_similarity.mjs CLI skill: scripts/similarity.mjs MCP tool: mcp__plugin_ruflo-core_ruflo__metaharness_similarity (registered in v3/@claude-flow/cli/src/mcp-tools/metaharness-tools.ts) Spike anchor: scripts/_spike-similarity.mjs (regression suite — invariants locked here)

Source: ruvnet/ruflo → plugins/ruflo-metaharness/skills/harness-similarity/SKILL.md

---name: harness-similaritydescription: ADR-152 — weighted similarity between two harness fingerprints (genome + score JSON). Returns overall score in [0,1] plus per-component breakdown (cosine over 9 numerics, categorical agreement over 4 enums, jaccard over agent_topology). Unblocks ADR-151 §3.2 Recommender, §3.3 Drift Detection, §3.5 Plugin Compat. Pure-TS, no `@metaharness/*` dep — preserves ADR-150's four architectural constraints.---Surfaces the production similarity function from [`scripts/_similarity.mjs`](../../scripts/_similarity.mjs) as a callable skill. Use when an agent needs to:- decide whether to fork an existing harness vs scaffold a new one- rank candidate templates against a target repo's genome- diff two harnesses produced by different teams to find duplicate work- generate the confidence number that ADR-151 §3.2's Recommender wraps## Algorithm (from ADR-152 §Decision)```overall = 0.60·cosine + 0.25·categorical + 0.15·jaccard```- **cosine** — over a 9-dim numerical vector of normalized scorecard + genome dims- **categorical** — fraction of 4 enum fields that match (`repo_type`, `archetype`, `template`, `recommendedMode`)- **jaccard** — `|A ∩ B| / |A ∪ B|` over the `agent_topology[]` arrayThe 3-component design is load-bearing: numerical cosine alone is too coarse (the iter-35 spike showed LEGAL vs DEVOPS at cosine=0.97 despite being unrelated verticals). Categorical + jaccard pull the composite to the correct ordering.## Reference outputs (iter-35 spike fixtures)| Pair | overall | cosine | categorical | jaccard ||---|---:|---:|---:|---:|| `LEGAL` × `LEGAL` (self) | 1.0000 | 1.0000 | 1.0000 | 1.0000 || `LEGAL` × `SUPPORT` | 0.8296 | 0.9987 | 0.7500 | 0.2857 || `LEGAL` × `DEVOPS` | 0.5840 | 0.9734 | 0.0000 | 0.0000 |Both invariants from ADR-152 §"Smallest demonstrable spike" hold:1. `similarity(X, X) === 1` exactly2. `similarity(LEGAL, DEVOPS) < similarity(LEGAL, SUPPORT)` (vertical affinity)## Architectural constraint inheritance (ADR-150)- **Removable** — pure-TS function, zero static `@metaharness/*` imports.- **Optional** — no new dep in `package.json`.- **Graceful** — malformed inputs emit `{ degraded: true, reason }` with exit code 2; never throws.- **CI-gate** — smoke step 17y locks the contract: module exports, spike fixtures reproduce, CLI dispatcher entry registered, MCP tool registered.## Usage```bash# File inputsnpx ruflo metaharness similarity --a a.json --b b.json# Memory inputs (records persisted by oia-audit.mjs)npx ruflo metaharness similarity --a-key harness-X --b-key harness-Y# Per-dimension breakdown (used by ADR-151 §3.2 Recommender)npx ruflo metaharness similarity --a a.json --b b.json --per-dimension# Alert when too-dissimilar (used by ADR-151 §3.3 Drift Detection)npx ruflo metaharness similarity --a a.json --b b.json --alert-below 0.5```## ImplementationProduction module: [`scripts/_similarity.mjs`](../../scripts/_similarity.mjs)CLI skill: [`scripts/similarity.mjs`](../../scripts/similarity.mjs)MCP tool: `mcp__plugin_ruflo-core_ruflo__metaharness_similarity` (registered in `v3/@claude-flow/cli/src/mcp-tools/metaharness-tools.ts`)Spike anchor: [`scripts/_spike-similarity.mjs`](../../scripts/_spike-similarity.mjs) (regression suite — invariants locked here)---**Source:** [`ruvnet/ruflo`](https://github.com/ruvnet/ruflo) → `plugins/ruflo-metaharness/skills/harness-similarity/SKILL.md`

Frequently asked questions