`skills:eval` was at 38/46 with several skills measuring 0-33%. The low
scores were mostly bad eval cases rather than bad descriptions, for two
reasons that were nowhere written down:
- The harness runs each case with `--max-turns 1`, so the skill has to be
the model's FIRST tool call. A prompt asking "how does X work here", or
naming a concrete file, sends the model to Read/Grep first — a better
answer to the question, scored as a miss. Every 0% case was one of these.
- `AGENTS.md` is resident on every turn, so a prompt it already answers is
answered without any skill and the case can never pass.
Replace the cases that measured the wrong thing, expand every model-invoked
skill from 3 to 5 positives (negatives kept) so one flake cannot cross the
threshold, and reshape `local-dev`'s description to the action-first form.
Add `docs/skill-authoring.md` with the case shapes that fire, the ones that
cannot, and the probe-then-measure loop.
RUNS=5 npm run skills:eval: 63/63 at or above threshold, 60 at 100%,
all 18 negatives clean.
Closes#2202
Signed-off-by: cliffhall <cliff@futurescale.com>
`release` is now the only skill reachable by name alone, which is right: nobody
cuts a release by implication, whereas "file an issue for this" and "triage the
new issues" are both ordinary prose instructions.
Eval cases committed for both; each measured 5/5 at RUNS=3. One initial case
was rebuilt rather than tuned: "file an issue for the flaky Storybook test"
scored 0% because its SUBJECT was unresolved — the model went off grepping for
which test was flaky instead of reaching for the filing procedure. A trigger
case must not make the model investigate before it can act.
The full eval across all nine model-invoked skills reports a cost worth having
in writing, and it contradicts the justification given for the previous flip.
Every negative case still passes 100%, so there is no over-triggering — but the
skills that were already model-invoked measurably LOST trigger rate:
`project-structure` fell from 100% to 0% on two cases (n=4) and `testing` from
3/5 to 2/5, while all six newly flipped skills measured 100%.
So the ceiling is attention, not characters: the listing sat at 2.8k of 4k
throughout, and "the budget is not tight" was the wrong reason to think flipping
was free. AGENTS.md now records this, and requires the FULL eval to be re-run
after any flip rather than just the new skill's own cases.
Two of project-structure's three cases are also the invalid-case pattern this
file already documents — `core/auth/` is described in the AGENTS.md tree, so a
model answering "which package owns the secret storage backends" without a skill
is correct rather than failing. `testing`'s cases are not, and it was the weaker
of the two before this change as well.
Signed-off-by: cliffhall <cliff@futurescale.com>
