agentsclimarketplace

Jtbd context explorer

Skill lishix520/jtbd-skills/skills/jtbd-context-explorer

Modular agent skills for Jobs-to-be-Done and Outcome-Driven Innovation research.

Install
npx -y skills add lishix520/jtbd-skills --skill jtbd-context-explorer

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 14 days oldThe repository was created 14 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Extract Jobs-to-be-Done context evidence from customer interviews, feedback, reviews, support tickets, or scenario descriptions. Use when asked to identify the circumstances that triggered a change, desired progress, current alternatives or workarounds, non-consumption, emotional or social signals, feature requests, constraints, competing solutions, and unanswered research questions. Do not use to define a Core Functional Job, calculate opportunity scores, or recommend product strategy.

SKILL.md

7.1 KB, ~1.4k tokens by cl100k_base, as published. Nobody here has run it

JTBD Context Explorer

Turn messy customer feedback into "what happened, how they do it now, where they get stuck, and what to ask next."


Use this when

  • You have customer interview transcripts, reviews, support tickets, or feedback notes and need to extract what actually happened.
  • You want to separate real-world constraints and workarounds from feature requests.
  • You need to identify non-consumption barriers or emotional/social context signals.

Don't use this when

  • You need to define a solution-free Core Functional Job statement (use jtbd-job-definer).
  • You want to evaluate Push, Pull, Habit, and Anxiety switching tensions (use jtbd-forces-analyzer).
  • You need quantitative market opportunity scores (use jtbd-opportunity-calculator).

Minimum input

  • Minimum Input: Raw customer text (interview notes, reviews, support tickets, or feedback quotes). If no source text is supplied, returns analysis_status: insufficient_input.

What you get

  1. Human Summary: A clear 5-point breakdown of what is happening, current workarounds, biggest constraints, likely problems, and next best questions.
  2. Structured Context Evidence: Categorized arrays for circumstances, desired_progress, current_approaches, non_consumption, feature_requests, constraints, and competing_alternatives.
  3. Unresolved Evidence Gaps: Key unanswered research questions.

Quick prompt

"Extract the customer context, current workarounds, and key constraints from this feedback: '[Paste feedback here]'."

What to do next

  • Want to analyze switching tensions? Pass extracted context to jtbd-forces-analyzer.
  • Ready to formalize a solution-free customer goal? Pass to jtbd-job-definer.

Scope

Extract evidence for:

  • Circumstance: A concrete situation, trigger, constraint, event, or change that creates pressure to make progress.
  • Desired Progress: A stated or strongly implied change from a current situation toward a better future situation.
  • Current Approach: What the person currently does, including a product, manual process, workaround, delay, delegation, avoidance, or doing nothing.
  • Switching Trigger: A reported event or threshold that made the current approach inadequate.
  • Non-Consumption: Evidence that the person does not use an available solution because it is inaccessible, unaffordable, too complex, unsuitable, unavailable, prohibited by policy, security-restricted, or not worth adopting.
  • Feature Requests: Statements proposing specific product capabilities, buttons, or tools.
  • Constraints: Time, money, policy, environment, access, skill, compatibility, privacy, safety, or organizational restrictions.
  • Competing Alternatives: Solutions, behaviors, workarounds, or "do nothing" approaches used to make progress.
  • Emotional Signal: Evidence of a desired feeling or avoided feeling.
  • Social Signal: Evidence about how the person wants to be perceived by another person or group.

Evidence Rules

  1. Preserve direct statements as excerpts with source IDs.
  2. Label every interpretation as inferred; never present it as direct fact.
  3. Strongly implied desired progress is ALWAYS status: inferred. Only explicit customer statements of intent are direct_evidence.
  4. Do not infer causal relationships when the source only shows correlation.
  5. Record proposed solution statements under feature_requests; do not convert a feature request into a validated Core Functional Job, current approach, or competing alternative without independent evidence.
  6. Do not treat a complaint as proof of a broad market pattern or non-consumption.
  7. Do not classify something as non-consumption unless the material shows absence, avoidance, inability, or refusal to use a relevant alternative.
  8. Treat emotional and social language as separate signals, not as Core Functional Jobs or ODI desired outcomes.
  9. Record contradictions rather than resolving them through guesswork.
  10. Return the smallest next research question that would reduce the most consequential uncertainty.

Output Format

human_summary:
  what_is_happening: ""
  current_workaround: ""
  biggest_constraint: ""
  likely_problem_to_verify: ""
  next_best_question: ""

analysis_status: evidence_extracted | insufficient_input

sources:
  - id: ""
    type: interview | review | feedback | support_ticket | scenario
    limitations: []

circumstances:
  - id: ""
    statement: ""
    status: direct_evidence | inferred
    evidence:
      - source_id: ""
        excerpt: ""
    assumptions: []
    constraint_ids: []

desired_progress:
  - id: ""
    statement: ""
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

current_approaches:
  - id: ""
    statement: ""
    type: product | manual_process | workaround | delegation | delay | avoidance | do_nothing | unknown
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

switching_triggers:
  - id: ""
    statement: ""
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

non_consumption:
  - id: ""
    statement: ""
    barrier_type: access | affordability | complexity | suitability | availability | policy_or_regulation | security_or_privacy | perceived_value | unknown
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

feature_requests:
  - id: ""
    statement: ""
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

constraints:
  - id: ""
    statement: ""
    type: time | money | policy_or_regulation | security_or_privacy | environment | access | skill | compatibility | privacy | safety | organizational | unknown
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

competing_alternatives:
  - id: ""
    statement: ""
    type: product | manual_process | workaround | delegation | delay | avoidance | do_nothing | unknown
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

emotional_signals:
  - id: ""
    statement: ""
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

social_signals:
  - id: ""
    statement: ""
    audience: ""
    status: direct_evidence | inferred
    evidence: []
    assumptions: []

contradictions: []
evidence_gaps: []
next_research_question: ""

Reference

Read references/context-exploration-rules.md before:

  • Categorizing proposed solutions into feature_requests
  • Deciding whether a phrase proves non-consumption vs doing nothing
  • Determining whether desired progress is direct_evidence or inferred
  • Separating an emotional signal from a social signal
  • Extracting top-level constraints

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.