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Get Started Free →Triage a competitive or market question into the right intelligence disciplines, cadence, and executing skill. Use when you know something needs researching but not which channel to run.
.claude/skills/deanpeters-intel-discipline-advisor/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-15 | ✗→✓ | ▲ Improved | 144% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -22% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 75% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 164% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 51% | 0% |
Triage a competitive or market question into the right intelligence response: which of the eight collection disciplines to run, on what cadence, feeding which artifact, executed by which skill. The intelligence-collection-disciplines compendium holds everything about every channel; this advisor answers the question a busy PM actually has — "given what's on my desk, which two or three channels matter, and where do my limited hours go?" Running every discipline on every question is the failure mode; scoping to the decision is the craft. The advisor teaches the mapping as it routes, so by your third session you won't need it. That's the goal.
Works best with: the decision or question on your desk, in your words — "I think Competitor A] is building something," "my TAM slide got shredded," "sales keeps getting surprised." Also useful: any signal you've already noticed (a job posting, a pricing change, an earnings remark), your time budget, and whether you're limited to free sources.
Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.
Arriving empty-handed? That works too. The advisor opens by asking what's on your desk, with enumerated situations to pick from.
Example invocation: Intel discipline advisor: two of their senior engineers just followed our CTO on a preprint server, and their careers page doubled — what do I run?
workshop-facilitation as thedefault interaction protocol (entry modes, one question per turn, progress labels, numbered recommendations). This file defines the domain logic.
intelligence-collection-disciplines:every PM artifact has a known discipline mix and refresh cadence. The advisor's job is matching the user's situation to a row — and showing the match, because the mapping is the lesson.
already flagged once — the recommendation starts from "1 discipline flagged" on the confidence stacking ladder and names which independent channels would corroborate (see autonomous-investigation).
releases change annually. A watch the user can't sustain is worse than none — it produces false confidence that someone is watching.
customers churn," the answer is win/loss interviews and discovery, not a patent sweep. The advisor says so.
This interactive skill asks 3 adaptive questions, then offers numbered, context-aware recommendations.
"What's the situation? Pick the closest, or describe your own:
post, a patent, a customer remark? (Whatever you saw is one discipline already flagging; we'll pick the independent channels that could corroborate it.)"
company's position in it?"
week, a half-day a month, a day a quarter?"
"Two quick constraints: free sources only or is paid tooling available, and any geographic focus? (Region changes which registries and statistics bureaus apply.)"
Synthesize and offer 3-5 numbered recommendations, each naming: discipline mix → cadence → executing skill → artifact fed, with one line on when it's the right choice. Always show why the disciplines were chosen (the mapping-table logic), and include the off-ramp when it's honest. Handle single selection, combinations ("1 and 3"), and custom directions per the facilitation protocol.
Routing quick-reference (from the artifact-mapping table):
| Situation | Discipline mix | Executing skill | |---|---|---| | Suspected move | Corroborate the seen signal: TECHINT + HUMINT + SIGINT + FININT, fused | intelligence-collection-disciplines fusion template, then competitive-intel-watch | | Battle card | SIGINT + OSINT + HUMINT | battle-card-builder, kept fresh by the watch | | TAM/SAM/SOM | GEOINT/DEMOINT + FININT capture rates | tam-sam-som-calculator Mode 3 | | Positioning / ICP | OSINT + GEOINT/DEMOINT (+ VoC) | voice-of-customer-miner → positioning-statement | | Industry structure | FININT + OSINT | porters-five-forces | | One company's position | OSINT + FININT + HUMINT | swot-analysis or company-intel | | Pricing question | SIGINT + FININT | pricing-packaging-tracker | | Macro exposure | GEOINT/DEMOINT + regulatory FININT | pestel-delta-monitor | | Standing watch | SIGINT weekly, OSINT+HUMINT monthly, FININT+TECHINT quarterly — scaled to stated capacity | competitive-intel-watch | | The full picture | All of the above, sequenced | competitive-analysis-process |
Close by offering the one-page triage card (template.md) filled in from the session — the route, its "because," and a review date, as a handoff artifact.
Sample flow (fictional):
> Q1 → User: "1 — I think Competitor A] is building a data-platform play." > Q2 → User: "Their careers page doubled, mostly data engineers." > Q3 → User: "Free sources, US only." > > "Your hiring observation means HUMINT has already flagged once — one discipline is an anecdote, > so the job is corroboration from independent channels. Recommendations: > > 1. TECHINT sweep this week (patents.google.com + their GitHub org + arXiv affiliations, free) — > a paper-or-patent cluster in the same specialty as the hiring surge is the strongest fusion pair > available. Pick this first: highest corroboration value per hour. > 2. SIGINT check, 30 minutes (crt.sh for new subdomains, Wayback diff on their product pages) — > catches launch staging if this is further along than hiring suggests. > 3. FININT pass at their next earnings call — listen for capex dodges and segment-language > shifts; free via their IR page. Slower, but turns hypothesis into briefable intelligence. > 4. Set the watch instead — if this can't get hours this quarter, wire Competitor A] into > competitive-intel-watch monthly and let the cadence catch it. > > Reply 1, 2, 3, 4, a combination like '1 and 2', or tell me more. (Two agreeing disciplines = working > hypothesis; three = brief your leadership.)"
The off-ramp in action: user picks "artifact: ICP refresh," but Q2 reveals the real question is "why did our last three enterprise deals stall?" The honest recommendation leads with win/loss interviews (HUMINT's ground-truth layer) and discovery-interview-prep — "no public-web sweep answers a question your own churned prospects can answer better."
See examples/conversation-flow.md for a full end-to-end session: inline input crediting two of the three questions, a capacity answer that gets believed, a combination selection, and a "tell me more" that earns a teaching answer. examples/conversation-flow-industrial.md shows the routing shift for a physical-world signal — permits and customs data instead of site diffs.
channels matched to the decision beats coverage theater — the mapping table exists so you can skip.
Recommending channels that re-detect the same signal type adds no corroboration; independence is what stacks.
capacity question and believe the answer.
lesson. Every recommendation shows its mapping-table logic — the user should leave better at triage, not just triaged.
tickets answer some questions better than any public-web sweep; say so when it's true.
intelligence-collection-disciplines (Component) — the compendium this advisor routes into; the pedagogic pairworkshop-facilitation (Interactive) — facilitation protocolautonomous-investigation (Workflow) — confidence stacking and evidence labels the recommendations lean oncompetitive-intel-watch, battle-card-builder, tam-sam-som-calculator, porters-five-forces, swot-analysis, voice-of-customer-miner, pricing-packaging-tracker, pestel-delta-monitor, competitive-analysis-processdiscovery-interview-prep (Interactive) — the off-ramp when the question belongs to discoveryintelligence-collection-disciplines.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-15 | fail→pass | 9,844 | 3,989 | -59% | 1 | 1 | 0% | 1,391 | 3,392 | +144% | 0 | 0 | — |
case-01 | fail→fail | 17,770 | 7,835 | -56% | 1 | 1 | 0% | 2,656 | 3,923 | +48% | 0 | 0 | — |
case-02 | fail→fail | 3,581 | 4,900 | +37% | 1 | 1 | 0% | 534 | 3,547 | +564% | 0 | 0 | — |
case-03 | fail→fail | 15,109 | 22,449 | +49% | 1 | 1 | 0% | 2,398 | 6,347 | +165% | 0 | 0 | — |
case-04 | pass→pass | 17,482 | 12,454 | -29% | 1 | 1 | 0% | 2,441 | 4,780 | +96% | 0 | 0 | — |
case-05 | fail→pass | 29,877 | 12,945 | -57% | 1 | 1 | 0% | 6,118 | 4,747 | -22% | 0 | 0 | — |
case-06 | fail→fail | 20,966 | 11,210 | -47% | 1 | 1 | 0% | 3,185 | 4,657 | +46% | 0 | 0 | — |
case-07 | fail→fail | 16,339 | 5,724 | -65% | 1 | 1 | 0% | 2,415 | 3,622 | +50% | 0 | 0 | — |
case-08 | fail→fail | 15,771 | 5,373 | -66% | 1 | 1 | 0% | 2,404 | 3,580 | +49% | 0 | 0 | — |
case-09 | fail→fail | 15,437 | 6,696 | -57% | 1 | 1 | 0% | 2,264 | 3,778 | +67% | 0 | 0 | — |
case-10 | fail→pass | 13,422 | 6,101 | -55% | 1 | 1 | 0% | 2,089 | 3,662 | +75% | 0 | 0 | — |
case-11 | fail→pass | 12,514 | 13,446 | +7% | 1 | 1 | 0% | 1,774 | 4,683 | +164% | 0 | 0 | — |
case-12 | pass→pass | 17,002 | 8,349 | -51% | 1 | 1 | 0% | 2,447 | 4,000 | +63% | 0 | 0 | — |
case-13 | fail→pass | 16,806 | 7,737 | -54% | 1 | 1 | 0% | 2,519 | 3,805 | +51% | 0 | 0 | — |
case-14 | fail→pass | 16,174 | 13,568 | -16% | 1 | 1 | 0% | 2,233 | 4,717 | +111% | 0 | 0 | — |
case-16 | fail→pass | 16,492 | 12,120 | -27% | 1 | 1 | 0% | 2,272 | 4,497 | +98% | 0 | 0 | — |
case-17 | pass→fail | 17,389 | 5,759 | -67% | 1 | 1 | 0% | 2,138 | 3,554 | +66% | 0 | 0 | — |
case-18 | fail→pass | 10,356 | 8,559 | -17% | 1 | 1 | 0% | 1,507 | 4,250 | +182% | 0 | 0 | — |
case-19 | fail→fail | 7,009 | 3,233 | -54% | 1 | 1 | 0% | 990 | 3,261 | +229% | 0 | 0 | — |
case-20 | pass→pass | 28,682 | 7,358 | -74% | 1 | 1 | 0% | 1,799 | 3,749 | +108% | 0 | 0 | — |
case-21 | pass→pass | 10,618 | 9,239 | -13% | 1 | 1 | 0% | 1,664 | 4,168 | +150% | 0 | 0 | — |
case-22 | fail→pass | 18,691 | 13,147 | -30% | 1 | 1 | 0% | 2,551 | 4,813 | +89% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +36 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/9/2026 | +50% |
Other measured skills in the registry, with their headline benchmark lift.