discovery-research Stinger

SkillDev tools

Continuous product discovery coach — Teresa Torres interview cadence, Opportunity Solution Trees, Jobs-to-be-Done interviews, prototype testing, and the "build less, learn more" loop. Use when the user says "run a discovery session", "build an OST", "write an interview script", "map our assumptions", "design a prototype experiment", "weekly discovery summary", or when a team is unsure what to build next and needs to run discovery before planning. Do NOT use for shipped-feature usability testing (quality-worker-bee), UI design decisions (ux-ui-worker-bee), PRD authorship (library-worker-bee), or analytics result interpretation.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the discovery-research Stinger skill

What this skill tells your AI

The instructions your AI receives, as published by legioncodeinc/vibe-coding-tools in src/skills/discovery-research-stinger/SKILL.md and read by ahel’s review.

Procedural arsenal for discovery-research-worker-bee, the Legion Army's continuous-discovery coach. This stinger encodes Teresa Torres' continuous-discovery framework, Opportunity Solution Trees (OST), Jobs-to-be-Done (JTBD) interview methodology, assumption mapping, and lightweight prototype experiment design.

The stinger's job is to give the Angel specific, opinionated playbooks — not generic UX theory. Every guide cites primary research. Every template is ready to fill in. Every example shows a real output shape.


When this stinger applies

Load this stinger when discovery-research-worker-bee is invoked. Typical triggers:

  • "Help me figure out what to build next."
  • "Create an opportunity solution tree for [product/team]."
  • "Write a user interview script for [opportunity]."
  • "Map the assumptions behind [solution]."
  • "Design an experiment to test [assumption]."
  • "We need to do customer discovery before writing the PRD."
  • "Run continuous discovery for [desired outcome]."

Do NOT load for:

  • Usability testing of shipped features → quality-worker-bee.
  • Authoring a PRD or feature spec → library-worker-bee.
  • UI/UX design decisions → ux-ui-worker-bee.
  • Analytics or experiment result interpretation → inline or future analytics Angel.

First action when this stinger is loaded

Read these in order before doing anything else:

  1. guides/00-principles.md — the continuous-discovery philosophy, the three tenets, the "build less, learn more" manifesto, and the critical directives.
  2. guides/01-desired-outcome.md — how to scope a desired outcome before any other work begins.
  3. guides/02-opportunity-solution-tree.md — OST node taxonomy, snapshot rules, common failure modes.

Then load domain-specific guides as the session requires:

  • guides/03-interview-cadence.md — when to run interviews and how to recruit.
  • guides/04-jtbd-interview.md — the Five-Act interview structure.
  • guides/05-assumption-mapping.md — DVFU 2×2 and Kill Zone protocol.
  • guides/06-experiment-design.md — prototype archetypes and success criteria.

Procedure (how the Angel uses this stinger)

1. Anchor to a desired outcome

If no outcome is stated, run the outcome-scoping interview from guides/01-desired-outcome.md. Nothing else starts until a single measurable outcome is defined.

2. Build or update the OST

Read or create library/discovery/opportunity-solution-tree.md using the structure from guides/02-opportunity-solution-tree.md and templates/opportunity-solution-tree.md.

3. Generate an interview script

For a target opportunity node, produce a JTBD-style script using guides/04-jtbd-interview.md and templates/interview-script.md. Write to library/discovery/interview-scripts/<YYYY-MM-DD>-<opportunity-slug>.md.

4. Map assumptions

For a chosen solution, run the DVFU 2×2 protocol from guides/05-assumption-mapping.md using templates/assumption-map.md. Write to library/discovery/assumption-maps/<solution-slug>.md.

5. Design an experiment

For the highest-risk assumption, design the smallest invalidating experiment using guides/06-experiment-design.md and templates/experiment-plan.md. Write to library/discovery/experiments/<YYYY-MM-DD>-<experiment-slug>.md.

6. Summarize for stakeholders (optional)

On demand, produce a one-page weekly discovery summary using templates/weekly-summary.md.


Critical directives

  • Never recommend building without at least one validated assumption test. Why: the "build less, learn more" loop exists to prevent building on wrong assumptions; skipping it is the failure mode continuous discovery is designed to catch. (Source: research/external/2026-05-20-torres-2026-roadmap-ai-discovery.md)
  • Always anchor work to a single desired outcome. Why: OSTs without a defined outcome become wish lists. (Source: research/external/2026-05-20-opportunity-solution-tree-guide-2026.md)
  • Distinguish opportunities (problems/desires) from solutions (product ideas). Why: conflating the two is the most common discovery anti-pattern. (Source: research/external/2026-05-20-opportunity-solution-tree-guide-2026.md)
  • Use Torres' weekly cadence as the default structure. Why: continuous discovery requires rhythm; ad-hoc interviews generate anecdotes, not patterns. (Source: research/external/2026-05-20-continuous-discovery-habits-operationalized-2026.md)
  • Ask "what's the story?" before coding any interview insight. Why: JTBD is story-based; jumping to themes before hearing the full narrative misses the motivation structure. (Source: research/external/2026-05-20-jtbd-switch-interview-moesta-method.md)
  • Do not produce a PRD or implementation plan. Why: that is library-worker-bee's job; hand off a validated opportunity + winning solution, not a spec.

Folder layout

discovery-research-stinger/
+- SKILL.md                          (this file)
+- README.md                         (one-page human overview)
+- guides/
|  +- 00-principles.md               (philosophy, three tenets, critical directives)
|  +- 01-desired-outcome.md          (outcome scoping, three-part test)
|  +- 02-opportunity-solution-tree.md (OST taxonomy, snapshot protocol, failure modes)
|  +- 03-interview-cadence.md        (weekly cadence, recruiting, structure)
|  +- 04-jtbd-interview.md           (Five-Act structure, forces diagram)
|  +- 05-assumption-mapping.md       (DVFU 2x2, Kill Zone protocol)
|  +- 06-experiment-design.md        (four archetypes, success criteria)
+- examples/
|  +- happy-path-saas-onboarding.md  (worked OST + interview + experiment for SaaS)
|  +- edge-case-b2b-stakeholders.md  (discovery in a complex B2B buying environment)
+- templates/
|  +- opportunity-solution-tree.md   (OST skeleton)
|  +- interview-script.md            (Five-Act script scaffold)
|  +- assumption-map.md              (DVFU 2x2 table)
|  +- experiment-plan.md             (experiment brief skeleton)
|  +- weekly-summary.md              (stakeholder summary one-pager)
+- reports/
|  +- README.md                      (describes what past-run summaries look like)
+- research/                         (populated by scripture-historian; DO NOT MODIFY)
   +- research-plan.md
   +- research-summary.md
   +- index.md
   +- internal/
   +- external/

Refresh cadence

  • The procedural guides (00- through 06-) align with Teresa Torres' continuous discovery framework (stable since 2021 Continuous Discovery Habits). Refresh when Torres publishes a major framework update or when a new OST tooling standard emerges.
  • The research folder covers the Nov 2025 - May 2026 window. Re-run scripture-historian at normal tier if a significant new source (e.g., a new Torres book/course, a major JTBD update from Moesta) emerges.
  • Templates are stable; no cadence refresh expected.

Command Brief: ai-tools/command-briefs/discovery-research-worker-bee-command-brief.md Part of the Legion Army forged by Mario Aldayuz a.k.a @thenotoriousllama.

Signals

GitHub stars
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Last commit
Sep 2026
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skill
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Source
github.com/legioncodeinc/vibe-coding-tools