Inspect evolved prompt configurations, validate their structure, and view the system prompts they produce. You can also classify failures in run transcripts to support reviews before adopting or changing an agent policy.
Inspect and audit GEPA genomes via the `@metaharness/darwin/gepa` library entry (darwin 0.8.0) — load/validate a genome (default is the shipped cand-6 promotion), render the system prompt a genome compiles to, or classify failure modes in a run transcript. The `gepaOptimize` loop itself is library-only (bring your own evaluator) and not surfaced here — use `harness-evolve` for sandbox-scored evolution. Degrades gracefully when @metaharness/darwin is absent.
harness-gepa inspects prompt configurations tuned through evolution so you can review them before introducing them to an agent. It loads configuration data called a GEPA genome, validates its structure, and displays the system prompt generated from those settings. It can also classify failure types in run transcripts. If you do not specify a file, it loads the included cand-6.
Use it before adopting a tuned configuration to see the actual instructions it will produce. It also helps when you want to validate configuration changes in CI or examine transcripts from runs that did not work as expected.
The skill uses @metaharness/darwin/gepa. If the library cannot be found locally, it attempts to install a pinned version. If installation is unavailable, it returns results with limited functionality. The optimization loop itself is outside this skill's scope. To run optimization, provide your own evaluation process and use the library directly, or use the separate harness-evolve skill.
This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.
AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.
The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.
Review the instructions the agent will receive before you install.
Surfaces the GEPA (genetic-evolution prompt-adaptation) library exports
from @metaharness/darwin/gepa. Unlike the other skills in this plugin
there is no CLI binary behind this — the script dynamic-imports the library
(local resolution first, versioned cache install as fallback) and calls the
subprocess-safe subset.
--op render shows the actual system
prompt a genome compiles to — read THAT, not the raw JSON, before
wiring a genome into a harness.--op genome loads + validates the shipped
cand-6 genome (first holdout-confirmed cheap-tier promotion; provenance
ships in the package) or any genome file you point at.--op validate --alert-on-invalid exits 1
on structural errors.--op analyze --transcript run.json classifies
failure modes (GEPA's failure-class taxonomy) from a transcript array.gepaOptimize — the optimization loop takes an in-process
evaluate(candidate) callback ("bring your own evaluator") that cannot
cross a subprocess boundary. Two supported paths instead:
import { gepaOptimize, loadCand6Genome } from '@metaharness/darwin/gepa'harness-evolve (darwin CLI evolve),
which pairs GEPA with its own sandbox evaluators.Implementation: scripts/gepa.mjs.
import('@metaharness/darwin/gepa'); on MODULE_NOT_FOUND fall back to a
one-time npm install --prefix ~/.ruflo/darwin-cache-<pin> and import
the cached dist/gepa/index.js (versioned dir → pin bumps invalidate).--op:
genome → loadGenome(fs, path) or loadCand6Genome() + validateGenomevalidate → validateGenome(rawJson) (raw parse so broken files reach
the validator instead of throwing in the loader)render → buildSystemFromGenome(genome, ext?, glob?)analyze → analyzeTranscript(entries)--alert-on-invalid, 2 on bad input).node scripts/gepa.mjs --op genome # cand-6 + validation
node scripts/gepa.mjs --op render | jq -r .system # what does cand-6 SAY?
node scripts/gepa.mjs --op validate --path my-genome.json --alert-on-invalid
node scripts/gepa.mjs --op analyze --transcript run.json
0 — op completed (or degraded — darwin not installable)1 — --alert-on-invalid and validation found errors2 — config error (unknown op, missing/broken input file)No reviews yet. Tell others what you thought.
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Compare models available through the HuggingFace router with chat-ui configuration, research missing models, and write short English descriptions of their architecture and capabilities. Add entries to both production and development configuration files and commit the changes.
Create an Architecture Decision Record, a document for recording important design choices, with the next sequential number. It generates a Markdown template, registers the record in AgentDB, and links related decisions found through search.
Build a searchable index and relationship graph from ADRs, records of architectural decisions. Import two supported document formats, refresh existing metadata without duplicate relationships, and review summaries of statuses, missing references, and inconsistencies.
Rebuild the index of ADRs, records of architectural decisions, after files or relationship lines are deleted. It clears stored records and relationships, indexes the files still present, and checks that the final record count matches.
Review code changes against accepted Architecture Decision Records, documents that capture agreed design choices. Report violations, outdated references, compliant changes, and areas without ADR coverage, then suggest code fixes or a new decision record where appropriate.
Check saved architecture decision records (ADRs) for broken references, circular replacement relationships, and inconsistent statuses. Use the results to verify imported records or stop a CI check when selected integrity rules fail.