Log Evidence Skill

The re-entry point after offline human work. Takes raw conversation notes, observations, or survey results and integrates them into the canvas with proper provenance.

When to Use

• After completing a human task from

  canvas/human-tasks.yml

• When the user returns from an offline conversation and has findings to record
• When SessionStart reminds about pending human tasks and the user has completed them
• When the user pastes conversation notes or interview summaries

Workflow

1. Check pending tasks:

   • Read

     canvas/human-tasks.yml

     for

     pending_tasks

   • List them: "You have [N] pending human task(s): [objective summaries]"
   • Ask: "Which task did you complete? Or paste your notes and I'll match them."

2. Guided evidence capture (if user doesn't have a filled template):

   • Who did you talk to? (role and context, not name -- privacy)
   • What did you learn? (open-ended first, let them tell the story)
   • Any direct quotes worth capturing?
   • Anything surprising or contradicting our current assumptions?
   • JTBD signals: functional job, emotional job, social job?
   • Any follow-up conversations needed?

3. Classify the evidence on Gilad's ladder:

   • Single conversation ->

     anecdotal

     (0.3)
   • 2 conversations with consistent signals ->

     anecdotal

     (0.3), note convergence
   • 3+ triangulated conversations ->

     data-supported

     (0.5-0.6)
   • Explain the classification: "One conversation is anecdotal evidence. We'd need 2-3 more to call it data-supported."

4. Update canvas provenance:

   • Identify the relevant canvas file and section (from the task's

     canvas_refs

     )
   • If the canvas entry has NO provenance object yet (early project), create one:

     provenance:
       evidence_type: anecdotal  # single conversation
       evidence_sources:
         - "interview-YYYY-MM-DD-[role-descriptor]"
       source_classes:
         - external_human
       captured_at: "YYYY-MM-DDTHH:MM:SSZ"
       confidence: 0.3
     

   • If provenance already exists: add to

     evidence_sources

     and

     source_classes

     arrays
   • Update

     evidence_type

     if the new evidence strengthens it
   • Update

     confidence

     score with explicit reasoning
   • Update

     captured_at

     timestamp

5. Update

   canvas/human-tasks.yml

   :
   • Move task from

     pending_tasks

     to

     completed_tasks

   • Record:

     completed_at

     ,

     evidence_logged_to

     ,

     key_findings

     ,

     source_class: external_human

Task Cancellation

If the user reports a task couldn't be completed (contact unavailable, timing didn't work, etc.):

1. Ask: "Should we cancel this task or reschedule it?"

2. If cancel: move to

   completed_tasks

   with

   source_class: cancelled

   and a note explaining why

3. If reschedule: update the task's

   objective

   or

   target_persona

   if needed, keep in

   pending_tasks

4. Either way: "The evidence gap still exists. Consider

   /handoff

   to plan an alternative approach."

5. Check for contradictions:

   • Compare findings against existing canvas data
   • If findings contradict assumptions: flag clearly
     • "This contradicts [canvas section / assumption]. The user said [X] but we assumed [Y]."
     • Suggest: "Consider running

       /devils-advocate

       to stress-test this assumption, or update the canvas with

       /canvas-update

       ."
   • If findings support assumptions: note the confirmation
     • "This supports [canvas section]. Confidence for [item] can increase."

6. Recalculate confidence:

   • Show before/after: "Diamond confidence: 0.45 -> 0.52 (added 1 external_human source)"
   • If this was the first external evidence: "First external human voice recorded. Evidence ratio improved from 0% to [X]%."

7. Suggest next steps:

   • If more conversations needed: "One conversation is a start. Consider

     /handoff

     for 1-2 more to reach triangulation."
   • If enough evidence: "Evidence looks solid for

     /diamond-progress

     to attempt the next transition."
   • If contradictions found: "Before progressing, resolve the contradiction. Run

     /devils-advocate

     or revisit the canvas."

Canvas Output

• Updates: relevant canvas file provenance (evidence_sources, source_classes, evidence_type, confidence)
• Updates:

  canvas/human-tasks.yml

  (moves task to completed)
• May update:

  canvas/opportunities.yml

  ,

  canvas/user-needs.yml

  ,

  canvas/jobs-to-be-done.yml

  depending on findings

Theory Citations

• Torres (CDH): Triangulation requirement (3+ sources for data-supported)
• Gilad (Evidence-Guided): Confidence ladder classification
• Christensen (JTBD): Functional/emotional/social capture structure
• Argyris (Double-Loop): Contradiction detection triggers assumption questioning