| name | night-market-research-methodology |
| description | Turn hunches into accepted results: worthiness score, evidence bar, research-to-rules. Use when vetting ideas. Not for QA; use night-market-validation-and-qa. |
Night Market Research Methodology
The discipline that turns a hunch into an accepted result in this
repo. An "accepted result" is a change that survived the evidence bar
and landed through change control as a rule, a skill module, a config
gate, or an ADR. Everything else is either a local working note or a
documented retirement. This skill covers the full path: score the
idea, experiment behind a default-off flag, meet the evidence bar,
land the durable artifact, or retire the idea on the record.
The evidence bar
A claim graduates from hunch to result only when it passes all four
tests.
-
One mechanism explains all observations, including negatives.
If the hypothesis explains the three failing cases but not why the
fourth case passed, it is incomplete. Keep digging until a single
mechanism accounts for everything you saw.
-
Predict numbers before running. Write down the expected
measurement first, then measure. In-repo anchor: the forced-eval
harness labels expected activations in
prototypes/forced-eval/activation_cases.json before any run,
then compares baseline against treatment with a McNemar paired
test (a significance test for paired binary outcomes).
-
Survive assigned adversarial refutation. Assign a reviewer or
agent whose explicit job is to break the claim. Use
Skill(attune:war-room) for hard-to-reverse decisions and
Skill(imbue:rigorous-reasoning) to counter agreement bias. A
claim nobody tried to break is unproven.
-
Never let the generator judge itself. The agent that produced
the work must not be its sole verifier. See
plugins/imbue/skills/proof-of-work/modules/independent-verification.md.
Prefer executable checks over an LLM judge, and prove the check
can fail before trusting it (Guards 2 and 3 in
plugins/imbue/skills/proof-of-work/modules/verifier-integrity.md).
Corollary from verifier-integrity: a green check proves the code
satisfies the spec as written. It cannot prove the spec says what you
meant, and it proves nothing if the check cannot fail. Validate the
spec separately from the code, and mutation-test the check itself.
Idea lifecycle
An idea moves through four gates in order. Skipping a gate is how
speculative infrastructure gets built and reverted.
Gate 1: score worthiness before building
Formula and thresholds from docs/backlog/queue.md (a local,
gitignored working file):
Worthiness = (Business Value + Time Criticality + Risk Reduction)
/ (Complexity + Token Cost + Scope Drift)
| Score | Action |
|---|
| > 2.0 | Implement now |
| 1.0 to 2.0 | Discuss before proceeding |
| < 1.0 | Keep in backlog |
Queue rules: at most 10 active items. Items untouched for 30 days are
archived to a GitHub issue (labels backlog,deferred) and removed
from the queue. Because docs/backlog/ and docs/research/ are
gitignored, the durable record of a deferred idea is the issue, not
the queue file.
Gate 2: experiment behind a default-off flag
Exemplar: the egregore completion-integrity gate.
- Commit
83281337 added the gate with
completion_integrity: bool = False in
plugins/egregore/scripts/config.py (still False as of
2026-07-02).
- Commit
cd903cbf added a test covering the raw-JSON opt-in path.
Pattern: land the mechanism off by default, cover the opt-in path
with a test, and collect usage before proposing a default change.
Gate 3: data-collection window before structural change
ADR-0015 (docs/adr/0015-orchestrator-skill-simplification.md)
requires 30 days of usage data before simplifying the over-built
orchestrator skills. Apply the same bar to any promotion or
simplification: name the data window in the PR, not an intuition.
Gate 4: adopt through change control or retire on the record
Adoption goes through the process in night-market-change-control.
Retirement is written down, never silent. ADR-0012 (confidence-tagged
claims) and ADR-0013 (Naur theory-building) carry Status: Superseded
by ADR-0017, which is Accepted and rules "Do not build an enforcement
mechanism. Permit voluntary use." A documented no is a valid result.
The research-to-rules pipeline
-
Run multi-channel research (Skill(tome:research) or manual) into
a dated synthesis at docs/research/YYYY-MM-DD-<topic>.md. Match
the shape of the existing docs: Thesis, What the evidence says,
solution pattern, Mapping to the night-market ecosystem, Evidence
gaps and caveats.
-
Map every gap against existing ecosystem assets before proposing
new code. Most gaps turn out to be covered already (see case
study 3).
-
Land each real gap as the smallest durable artifact: a
.claude/rules/ file, a module inside an existing skill, or a
config gate. A new skill is the last resort
(.claude/rules/shared-utility-consumer-rule.md requires 2+
consumers within 30 days).
-
Fold the load-bearing evidence out of the synthesis and into the
artifact that relies on it, as a table of sources and findings with
resolvable identifiers (arXiv IDs, URLs), plus the caveats that
bound them. Then delete the citation to the research file.
Caution: docs/research/ and docs/superpowers/ are both gitignored,
so a tracked doc that cites a path under either is a dangling reference
for every checkout but the author's. Step 4 is what prevents this, and
it is not optional. Five syntheses were folded back into their consumers
on 2026-07-27 for exactly this reason, and a brainstorm design record
cited by .claude/rules/ceremony-requires-need.md survived that pass
because the check below only looked at docs/research/. Verify with:
rg -o --hidden 'docs/(research|superpowers)/[A-Za-z0-9._/-]+\.md' \
-g '!docs/research/**' -g '!docs/superpowers/**' -g '!.git/**' . \
| sed 's/.*://' | sort -u \
| while read -r p; do
git check-ignore -q "$p" && echo "DANGLING: $p"
done
docs/backlog/ is gitignored too but stays out of the alternation on
purpose. Every tracked citation of it is framed as a local convention,
which .claude/skills/night-market-docs-and-writing/SKILL.md states
outright, so adding it here would report three intentional hits and
train the next reader to skip the output.
The failure it does invite is different, and ADR-0019 nearly shipped it:
a tracked doc of record delegating its content to a gitignored path.
Citing the backlog as the local ranking list is fine. Saying "the design
is recorded in docs/backlog/queue.md" is not, because on a fresh clone
nothing is recorded anywhere. A doc of record carries its own content.
Silence means every cited background path resolves on a fresh clone.
The check tests whether the cited path is gitignored rather than
matching on filename shape, so {session}-style templates in tome's
own docs do not trip it. Add any newly ignored docs directory to the
alternation, or the next draft cited from a rule repeats this.
The research doc is background, not the record.
Case study 1: coming loop (one doc, two artifact types)
The 2026-07-01 synthesis of Armin Ronacher's "The Coming Loop" pulled
in the METR randomized trial (arXiv 2507.09089: 16 developers, 246
tasks), GitClear 2025 (211M changed lines), and Karpathy's "mortal
terror of exceptions". It produced two artifacts:
- a review-time rule,
.claude/rules/prefer-invariants-over-fallbacks.md
(commit 9f771794), and
- a runtime gate, egregore
completion_integrity, default off
(commit 83281337).
Lesson: one research doc can fan out into different artifact types.
Match the artifact to where the failure occurs (review time versus
runtime).
Case study 2: prover-verifier (module, not skill)
The 2026-07-01 prover-verifier synthesis landed as commit 29081fda:
a 146-line module with six guards,
plugins/imbue/skills/proof-of-work/modules/verifier-integrity.md,
inside the existing proof-of-work skill. No new skill was created.
Lesson: extend the consumer that already exists.
Case study 3: karpathy-derivation (build only the delta)
docs/karpathy-derivation/project-brief.md (tracked in git) maps
four Karpathy principles against existing skills in a coverage matrix
and concludes "~90% coverage exists." Only the delta was built:
imbue:karpathy-principles, a compact synthesis with an anti-pattern
catalog. The same matrix was later reused as the lens for the April
2026 skill audit. Lesson: run the coverage analysis first. The most
common honest research outcome is "we already have this."
The audit protocol
As practiced in Discussion #449, the April 2026 skill-audit synthesis
(category [Knowledge]).
-
Tier 1 first: git history and rg scans
(Skill(pensive:tiered-audit)). Escalate only what Tier 1 flags.
-
Targeted parallel agents require output contracts, per
.claude/rules/plan-before-large-dispatch.md (plan mode at 4+
agents). Contract schema in
plugins/imbue/skills/proof-of-work/modules/output-contracts.md:
required_sections, min_evidence_count (minimum [EN] evidence
tags in findings), strictness (strict/normal/lenient). Findings
carry file:line evidence. An empty findings list is a valid
result. Report "no findings" as such rather than padding.
-
Findings land as waves of inline fixes.
-
Policy-shaped findings become issues, and landed issues become
rules. Issues #454 (Exit Criteria required in every SKILL.md) and
#457 (utility skills need 2+ consumers) both followed this path,
are CLOSED, and live on as .claude/rules/skill-exit-criteria.md
and .claude/rules/shared-utility-consumer-rule.md.
-
The deferred remainder gets a tracking issue: #574 (Wave-3
skill-audit backlog, OPEN as of 2026-07-02).
Reading Discussions requires GraphQL. The gh discussion subcommand
does not exist:
gh api graphql -f query='query {
repository(owner: "athola", name: "claude-night-market") {
discussion(number: 449) { title body }
}
}'
Proof-and-analysis recipes
Activation lift: does a skill actually fire?
prototypes/forced-eval/ (commit 5683e89b) measures whether a
forced-evaluation hook lifts skill activation:
activation_cases.json holds labeled prompts with expected
Skill() activations, recorded before measurement.
measure_activation.py runs each prompt via claude -p --output-format stream-json --max-turns 1 --allowedTools Skill,
baseline (hook off) against treatment (hook on), and applies the
McNemar paired test. True-negative cases count false activations,
so a high positive rate alone is not treated as success.
Status: PROTOTYPE, not wired into any plugin.json. The harness is
unit-tested but the live lift is unmeasured as of 2026-07-02 (the
README says so). Run the harness tests:
uv run python -m pytest prototypes/forced-eval/ -q
Verified 2026-07-02: 20 passed.
Mutation testing: are the tests real?
Mutation testing mutates source code and checks whether the tests
notice. A surviving mutant is a test that cannot fail on that
behavior, which is the "hollow check" failure mode from
verifier-integrity Guard 2. CI runs it weekly plus on dispatch
(.github/workflows/mutation-testing.yml). Exit codes: 0 means no
survivors, 2 means survivors found, anything else is a crash. Local,
per plugin:
cd plugins/<plugin>
uv pip install mutmut --quiet
uv run mutmut run --paths-to-mutate=scripts/,src/ --tests-dir=tests/
Adjust --paths-to-mutate to the directories that exist. CI builds
the list from the plugin's top-level scripts/ and src/ dirs.
Ratchet baselines: debt burndown you can prove
A ratchet baseline freezes today's debt count in a JSON file. The
check fails only when new debt appears, and prints when the count
drops so you can tighten the baseline and lock the win. Two live
ratchets, both pre-commit hooks and standalone scripts:
python3 scripts/check_skill_graph_drift.py
python3 scripts/check_skill_exit_criteria_drift.py
Verified output on 2026-07-02: dangling Skill() refs at 5 against a
baseline of 31, and SKILL.md files missing Exit Criteria at 1 against
a baseline of 127. Each script names the baseline key to lower. The
shrinking baseline diff is the burndown proof: cite it in the PR.
Where good ideas came from
| Source | Path taken |
|---|
| External research | Ronacher, METR, Karpathy syntheses became rules and gates (case studies above) |
| PR-review pain | Recurring finding classes became pre-commit guards and .claude/rules/ entries |
| Audits | Discussion #449 became issues #454/#457, which became rules |
| Incident lessons | See night-market-failure-archaeology for the chronicle |
When NOT to use
- Running tests, coverage, or the evidence gates for a concrete
change: use night-market-validation-and-qa instead.
- Classifying, gating, and landing a change: use
night-market-change-control instead.
- Mechanics of Discussions, the decision journal, or ADR practice:
use night-market-collective-memory instead.
- Understanding settled incidents and reverts: use
night-market-failure-archaeology instead.
- Choosing an open problem worth attacking: use
night-market-research-frontier instead.
- Executing the completion-integrity work: use
night-market-completion-integrity-campaign instead.
Exit Criteria
Provenance and maintenance
Compiled 2026-07-02 against repo v1.9.15, branch
discussions-fix-1.9.14. Commit anchors (9f771794, 83281337,
cd903cbf, 29081fda, 5683e89b) are stable. Volatile facts and
one-line re-verification:
- completion_integrity still default False:
rg -n "completion_integrity" plugins/egregore/scripts/config.py
- Ratchet counts (5/31 dangling refs, 1/127 missing Exit Criteria on
2026-07-02): rerun
python3 scripts/check_skill_graph_drift.py
and python3 scripts/check_skill_exit_criteria_drift.py
- Issue states (#454 CLOSED, #457 CLOSED, #574 OPEN on 2026-07-02):
gh issue view 574 --json state -q .state
- Forced-eval lift still unmeasured:
rg -n "not measured" prototypes/forced-eval/README.md
- Background doc dirs still gitignored:
git check-ignore docs/research docs/backlog docs/superpowers
- Mutation exit-code semantics:
rg -n "Exit codes" .github/workflows/mutation-testing.yml
- Worthiness thresholds: reread
docs/backlog/queue.md. It is a
local file, absent on fresh clones. The thresholds are restated
above.