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KohulanKohulan/orthonym-skills/skills/council/SKILL.md

council

Skill2 starsChanged 47 days agoMITView on GitHub

Answers a strategy or judgment-call question by re-deriving its load-bearing numbers first, then weighing the options through three or more distinct expert voices, then making one call with the condition that would flip it. Use when the user asks a strategy, prioritization, or judgment-call question — which option, what to work on next, is X worth it, should we do A or B, your call, show me the options, what's the best move, is this the right approach — or any decision that rests on a number, estimate, or recommendation that would otherwise be taken on trust. Not for ranking an eval run's failure classes (use cluster-failures) or for a second opinion on a finished plan before it ships (use fable-review).

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The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 128 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    After the evidence is in, give the decision three or more distinct voices, each reasoning only from the evidence just gathered, each free …

    line 43
  2. Distinctive:

    Always use this order, leading with the call:

    line 59
  3. Distinctive:

    No council of yes-men: If every voice agrees instantly, you under-searched or you are steering to the expected answer.

    line 79

“Common” is measured: kept by at least 6 in 10 of the 128 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Council

Overview

A strategy question is not answered from what you already know. It is answered by searching first, then convening a council of distinct expert voices, then making one call.

Core principle: every load-bearing number or claim — in the question, the handoff, memory, or a planning note — is a hypothesis until you re-derive it from ground truth this turn. A single well-reasoned voice is exactly how a false premise ships. The council exists so that one voice attacks another before the answer reaches the user.

Why this is a hard rule: "concentrated ROI" pools in chemistry projects routinely over-count 15–50× (e.g. a curated list of "~100 candidate defects" that turns out to have 2 genuine instances on re-derivation; "124 flagged structures" that turns out to be ~6 genuine). A baseline test of this exact skill's absence: three capable agents given one strategy question produced three different recommendations, one built entirely on an unvalidated number. Search + council makes the answer convergent instead of a coin-flip.

The protocol (do these in order)

1. Search before you weigh — validate the premise

  • Extract every load-bearing claim from the question and from your loaded context (handoff, memory, planning notes). Treat each as a claim to test, not a fact.
  • Give each independent facet its own investigator, run in parallel (parallel Agent calls); check a facet you can settle in a handful of tool calls inline. The standard three facets for a "should we do X?" question:
    1. Validate the headline number for X (re-derive the reachable win from ground truth).
    2. Size the alternative (what does the road-not-taken actually offer?).
    3. Assess X's risk (blast radius, determinism/regression surface, effort).
  • In your project, ground truth = your evaluation corpus/benchmark results, your run ledger, and the pipeline probed directly (any shortcuts/caches off, reproduce-first), not the tag/heuristic count in a note.

2. Convene the council — at least three named voices

After the evidence is in, give the decision three or more distinct voices, each reasoning only from the evidence just gathered, each free to disagree:

  • 🛠️ Senior Engineer — feasibility, blast radius, determinism/regression risk, effort, root-cause vs band-aid, does it fit the codebase's grain.
  • 📊 Product Manager — reachable wins, ROI, milestone fit, opportunity cost, what actually moves the metric the user cares about.
  • 🔬 Skeptic / QA — attacks the premise and the numbers, names what is still unverified, hunts the hidden coupling and the failure mode nobody priced in.
  • ➕ Add a domain expert or user-advocate voice when the decision turns on one.

Each voice is 1–3 sentences with its own read and may reach a different conclusion. Surface real disagreement rather than manufacturing consensus.

3. The chair synthesizes — the answer the user reads

Always use this order, leading with the call:

  1. The call — one option, stated first, unmissable.
  2. Confidence + the single biggest remaining uncertainty.
  3. All options side by side — a compact table (reachable wins / risk / effort). They asked to see the options; show them.
  4. What would flip the call — the one observation that would change the answer.

The search and the council voices follow the call, as its support.

Scale to the stakes

DecisionSearchCouncil
Small / easily reversibleinline parallel probesbrief 3-voice, terse
Milestone / expensive / hard to reverseone parallel investigator per facet3–4 voices, explicit disagreement

Rules

  • A number you did not re-derive this turn is not evidence — it is a claim to test.
  • No council of yes-men. If every voice agrees instantly, you under-searched or you are steering to the expected answer. Add the skeptic's strongest counter and check it.
  • Make the call. "It depends" / "both are fine" is not an answer. State the call and the condition that would change it.

Rationalizations — stop if you catch one

ExcuseReality
"I probed a couple examples, that's enough."Confirming a class "fails closed" ≠ counting the reachable win. Size the whole pool.
"They're clearly leaning toward X."Steering to the expected answer defeats the point. Weigh the evidence, then be willing to tell them they're wrong.

Worked examples (illustrative)

Q: "Fix the low-confidence-prediction cluster, or ship the pending featurizer refactor — your call?" The handoff said the cluster = "~100 rows, one root cause." Call: ship the featurizer refactor first, targeting its low-risk sub-fix. Confidence: high; biggest uncertainty: whether the cluster gates a future model family.

OptionReachable winsRiskEffort
Featurizer sub-fix~45lowsmaller
Cluster fix2moderate+ (determinism)larger

Flips if: the cluster turns out to gate a future model family — then build the contained half only. Search (3 parallel investigators): a corpus scan finds 2 genuine reachable wins from a targeted cluster fix (most tagged rows are out-of-domain scaffolds the model was never trained on); the ledger shows ~45 low-risk wins from the featurizer refactor's smaller sub-fix; a code trace shows the cluster fix un-masks a determinism defect in a shared normalization step (moderate+ risk). Council: 🛠️ "2 wins behind a determinism-sensitive guard is a bad trade." 📊 "2 vs ~45 reachable — not close." 🔬 "The ~100 was another over-counted pool."

Q (small, reversible): "Batch size 32 or 64 for tonight's retrain?" Call: 64. Confidence: medium; the run ledger shows both prior runs at 64 converged. Options: 32 (slower) / 64 (half the wall-clock). Flips if: out-of-memory at 64. Council: 🛠️ "Fits in memory." 📊 "Halves the wall-clock." 🔬 "Only two prior runs."

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