CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

interview-mapper

Maps a single interview transcript into a verbatim-grounded, lens-coded structure and checks whether analytic conclusions hold across independent re-runs. Use when the user wants to code, map, interpret, or make sense of an interview transcript, depth interview, custdev/JTBD/expert/usability/exit/win-loss/focus-group session, or wants cross-interview synthesis (insight cards, patterns) built up from coded transcripts — even if they don't name a method. Every conclusion must carry a verbatim quote verified against the source text; unstable conclusions are flagged for a human, never resolved by a single silent pass. Not for generating new interviews, not for plain audio transcription, and not for research-method or sample-size planning above the transcript (see product-research).

75

Quality

94%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strong, highly actionable skill body: concrete commands with flags, an explicitly sequenced pipeline with validation checkpoints and human-in-the-loop feedback at every fragile step, and honest limits/anti-patterns that read as a real checklist. The main weaknesses are mild redundancy around the 'unvalidated on real data' caveat and an undiscovered assets/example-outputs/ directory.

Suggestions

Consolidate the near-duplicate 'treat the first real run as a pilot / not validated on real data' guidance — currently stated in 'Exercise status' and in two separate 'Honest limits' bullets — into a single place to save tokens.

Add a one-line pointer to assets/example-outputs/ (journey-map, personas, insight-cards, etc.) so those five example outputs are discoverable from SKILL.md.

Soften or contextualize the '../product-research/SKILL.md' link so the boundary description does not depend on a path that may not resolve in every checkout.

DimensionReasoningScore

Conciseness

The body is dense and assumes competence — no basic-concept explanations, commands given inline, detail delegated to references. But the 'treat the first real run as a pilot / not validated on real data' guidance is repeated nearly verbatim in 'Exercise status' and twice in 'Honest limits', and the anti-patterns list slightly overlaps the honest-limits section — minor tightening available. Anchor 4 ('efficient; minor instances that could be trimmed') fits better than 5 because of this redundancy.

4 / 5

Actionability

Fully executable guidance: every workflow step is a concrete command with flags ('python3 scripts/route.py --goal <goal> --respondent <who>', 'verify_quotes.py --transcript t_nl.txt --claims claims.json', 'consensus.py run1.json run2.json run3.json', 'score_insights.py nuggets.json --k 3'), a copy-paste bash block shows sample invocations, and all 15 scripts are stated to be stdlib-only with '--help', '--sample', and '--output {human,json}'. Common cases are covered.

5 / 5

Workflow Clarity

The S0-S8 pipeline is explicitly sequenced with validation checkpoints at every stage (S1 transcript QA, S2 quote verify + entailment check, S3 reliability council flagging disagreement, S6.5 triangulated scoring with a >=k gate). Feedback loops are explicit ('If there's no exact quote, write NO QUOTE', flagged cells go to a human blind, calibrate thresholds on your own gold-set), and the anti-patterns section acts as an error-checklist — matching anchor 5.

5 / 5

Progressive Disclosure

Good structure: the overview stays compact, with well-signaled one-level-deep references ('Full routing matrix...: references/intake.md', 'Full detail: references/pipeline.md and references/synthesis.md'), and all referenced files exist with no nested reference chains. Two minor gaps keep it below 5: the five files in assets/example-outputs/ are never referenced anywhere in SKILL.md or references/ (undiscoverable), and '../product-research/SKILL.md' cannot be resolved from this bundle. Anchor 4 ('minor organization gaps') is the best fit.

4 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: third-person voice, concrete capabilities, explicit 'Use when' triggers with rich synonyms, and explicit exclusions that delimit it from adjacent skills (transcription, interview generation, method-level planning). Each clause carries routing or capability information rather than padding.

DimensionReasoningScore

Specificity

Multiple concrete actions are named: 'Maps a single interview transcript into a verbatim-grounded, lens-coded structure', 'checks whether analytic conclusions hold across independent re-runs', plus quote verification and cross-interview synthesis (insight cards, patterns). Coverage is comprehensive for the stated domain, matching the anchor-5 example's breadth.

5 / 5

Completeness

Explicitly answers both: what ('Maps a single interview transcript into a verbatim-grounded, lens-coded structure and checks whether analytic conclusions hold across independent re-runs') and when ('Use when the user wants to code, map, interpret, or make sense of an interview transcript...'), with concrete trigger phrases. It also adds explicit negative scope ('Not for generating new interviews, not for plain audio transcription...').

5 / 5

Trigger Term Quality

Natural trigger terms are comprehensively covered with synonyms: 'interview transcript', 'depth interview', 'custdev', 'JTBD', 'expert', 'usability', 'exit', 'win-loss', 'focus-group session', 'code, map, interpret', and 'insight cards'. It even catches users who 'don't name a method'. No relevant file-extension triggers exist for this domain.

5 / 5

Distinctiveness Conflict Risk

Clear niche (transcript-level coding and verification) with explicit boundary markers: 'Not for generating new interviews, not for plain audio transcription, and not for research-method or sample-size planning above the transcript (see product-research)'. This actively routes adjacent intents to the right skill, minimizing conflict risk.

5 / 5

Total

20

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 1 deeper-than-1-level

Warning

Total

15

/

16

Passed

Repository

alirezarezvani/claude-skills

Path

research-ops/skills/interview-mapper/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.