Imported from docxology/Skillarum (
data/evaluation/AGENTS.md). Install upstream withnpx skills add docxology/Skillarum --skill evaluation. Copyright stays with the author.
data/evaluation/ agent guidance
Overview
This directory holds the declarative evaluation plan and, when humans produce
them, the rating files that feed Skillarum's research layer. It contains plans
and judgments — never crawl state, never generated observations. Observations
are derived from run manifests under output/ by skillarum evaluate.
File organization
| File | Kind | Purpose |
|---|---|---|
cases.yaml |
tracked plan | The live case matrix: schema_version: 1 plus seven cases[] entries |
README.md |
doc | Quick reference |
AGENTS.md |
doc | This file |
Rating CSVs (for example rater-1.csv, rater-2.csv) and JSON adjudication
files are written here by humans when a rating round happens. None are present
in this checkout; do not fabricate them.
cases.yaml schema
Each entry declares: id, label, profile_id, target_id, source, and
repetitions. The seven declared cases are:
| Case id | Profile | Target |
|---|---|---|
math-three-minds |
math4wisdom |
three-minds |
math-three-minds-exposition |
math4wisdom |
three-minds-exposition |
math-minds-research |
math4wisdom |
minds-research |
aii-institute-overview |
active-inference-institute |
institute-overview |
aii-foundations |
active-inference-institute |
institute-foundations |
aii-programs |
active-inference-institute |
institute-programs |
aii-projects |
active-inference-institute |
institute-projects |
profile_id and target_id must match the id fields in
../sources/. The plan states intent; it does not assert that a
run occurred.
Usage
Run from the project root.
Generate a blank rating file
uv run python -m skillarum research ratings-template \
--output data/evaluation/rater-1.csv \
--case math-three-minds --case aii-institute-overview --json
--case is repeatable and required. Repeat the whole command with a different
--output per rater.
Aggregate observations against the case plan
uv run python -m skillarum evaluate --output-dir output \
--cases data/evaluation/cases.yaml --json
--cases already defaults to data/evaluation/cases.yaml.
Score with two independent rating files
uv run python -m skillarum evaluate --output-dir output \
--ratings data/evaluation/rater-1.csv \
--ratings data/evaluation/rater-2.csv --json
Validate an adjudication against the exact files used
uv run python -m skillarum research validate \
--ratings data/evaluation/rater-1.csv \
--ratings data/evaluation/rater-2.csv \
--adjudication data/evaluation/adjudication.json --json
Rules
- ✅ Two independent completed rating files are required before agreement is reported. Agreement stays pending if the files share no case ids.
- ✅ Substantive judgments carry evidence notes or source URLs.
- ✅ An adjudication names the case, criterion, both rater ids, the final 0–4 score, the adjudicator id, a rationale, and evidence URLs.
- ❌ Never fill the tracked plan with invented or placeholder scores.
- ❌ Never submit duplicate
(case_id, rater_id)rows; the CLI rejects them. - ❌ Never relabel a fixture observation as
live.
The validator checks that every adjudication refers to actual rows in the
associated rating files. When --ratings is omitted for an adjudication check,
the conventional sibling ratings.csv is used only as a compatibility fallback.
See also
README.md— quick reference../AGENTS.md— the data tree as a whole../sources/AGENTS.md— whereprofile_id/target_idcome from../../docs/evaluation.md— evidence tiers, statistics policy, publication flow