From pqa
Use when flagging branch conviction or calibrating instinct against outcomes.
How this skill is triggered — by the user, by Claude, or both
Slash command
/pqa:conviction-signallingThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Conviction ("the wormhole") is the harness's honest channel for instinct: a generator
Conviction ("the wormhole") is the harness's honest channel for instinct: a generator that believes in a non-obvious branch can say so, and the system protects that branch from early pruning — without ever letting belief decide acceptance. Effect on exploration, never on acceptance: that line is the invariant the design rides on.
One line, machine-parsed (regex in pqa/signals.py; byte-identical copy in
hooks/precipitate_capture.py — change both together):
conviction: high, basis: <one sentence naming the non-obvious reason this works>
high | medium | low. Only high protects from early pruning
(Conviction.protects_from_pruning).basis is mandatory and must name a mechanism: "burst absorption beats rejection
for this producer mix" calibrates; "feels clean" does not.conviction/basis fields, so the orchestrator,
the capture hook, and the engine all see one story.| Stage | Effect of conviction: high |
|---|---|
| collision (early pruning) | protected — cannot be dropped for "looking weak" before attack completes |
| adversary | attacked HARDER, not softer — calibration needs the stress |
| verification | nothing; the verifier does not read it |
| collapse | nothing; BranchResult.conviction is telemetry, and scripts/check_invariant.py statically forbids it from entering _rank_key |
| taxonomy / calibration | everything — signals joined to outcomes are the moat |
high only if you would defend the branch under
attack. Faked conviction is exposed by calibration and the harness learns to
discount you — the signal's entire value is its honesty.pqa.memory.record_signal(conn, session, level, basis, branch=...) — the precipitate-capture hook does this automatically for subagent
transcripts that contain the conviction line.update_signal_outcome(conn, signal_id, survived=..., verified=..., won=...). A finished run with outcome-less signals is
a calibration loop with no data — never leave them unfilled.pqa-self-reflector joins
signals to outcomes and emits P(win | conviction=high) vs P(win | no signal). That
number — not the feeling — is the empirical answer to "do hunches mean anything
here?"b2 (scout) digests back: conviction: high, basis: callers can shed load better than any limiter because only they know what's droppable.
verified: false.high, basis verbatim); outcome survived=true, verified=false, won=false; failure row carries conviction: high.Five runs later the calibration table shows high-conviction branches winning at 2× the no-signal base rate in this repo — the instinct is real here, and protecting it next spawn is justified by data. Or it shows 0.5× — and the harness starts discounting. Either answer is the system working as designed.
npx claudepluginhub aura-farming/pqa --plugin pqaProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.