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outcome-framing-coach

Reframe work from output/activity language to outcome language, on two surfaces — backlog items (Jira Epics and the like, classified on the Input→Activity→Output→Outcome→Impact taxonomy) and leadership asks (the drive-by directive that names a solution instead of a problem). Use when reviewing backlog epics in bulk, facilitating PI planning, running a value orientation audit, coaching a product owner on outcome-driven planning, or pressure-testing a message before a leader sends it. For whether an initiative is ready to commit rather than how it is worded, use sniff-test. If the question is broad — AI pilots with no clear return, or "where do we start" — run ai-activity-to-impact first; it finds the constraint and routes here.

Quality

79%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/outcome-framing-coach/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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.

The body delivers a genuinely actionable coaching method with a crisp taxonomy, concrete templates, worked examples, and thoughtful gotchas — clearly above average instruction-skill quality. Its main deductions are padding in the at-scale anecdote and Source sections, time-sensitive model-tier commentary, and dangling references to bundle files (scripts/, agents/) that are not shipped.

Suggestions

Ship the referenced files or remove the sections that point to them: 'scripts/prioritize_issues.py', 'agents/openai.yaml', and '../../CREDITS.md' are all cited in the body but absent from the bundle, leaving broken navigation and a non-runnable command.

Tighten the 'At-Scale Classification' section: compress the multi-sentence 9/13-anecdote caveat into one line and move the dated Haiku/Sonnet tier commentary into a versioned or deprecated note so time-sensitive claims don't pad the evergreen body.

Move the Rovo Agent Configuration block and Conversation Starters into a references file (e.g., references/rovo-config.md) so SKILL.md stays a lean overview with one-level-deep pointers.

DimensionReasoningScore

Conciseness

The core material (taxonomy table, smell list, gotchas, workflow) is tight and skill-specific, but the body includes unnecessary padding: a multi-sentence statistics caveat about a 13-item anecdote, dated model-tier commentary ('Haiku is adequate…', 'Model names and tiers also date fast') that is time-sensitive, and a Source section that repeats the same URL twice. This fits 'mostly efficient but could be tightened' better than the minor-trims level 4.

3 / 5

Actionability

Guidance is largely executable — a concrete rewrite template, a worked before/after example, a quarterly-bucket regex, and copy-paste bash commands. The gap: the 'Local Workspace Issue Prioritization' section instructs running 'python3 scripts/prioritize_issues.py' but no scripts/ directory exists in the bundle, so that command cannot actually be executed.

4 / 5

Workflow Clarity

The main coaching flow is a clear six-step sequence (Receive → Classify → Flag → Suggest → already-outcome branch → KPI guardrail), and the bulk-classification section supplies post-processing rules and a spot-check methodology, so batch operations do have verification guidance. Minor validation gaps (e.g., no explicit loop for re-checking a misclassified batch) keep it below 5.

4 / 5

Progressive Disclosure

The two references files (detection-patterns.md, rewrite-patterns.md) are well-signaled and one level deep with clear purpose statements, but three paths referenced in the body — scripts/prioritize_issues.py, agents/openai.yaml, and ../../CREDITS.md — do not exist in the bundle, and the Rovo Agent Configuration and Conversation Starters blocks are inlined host-paste content that could live in a separate file. Dangling references plus inlined secondary content place this between the 'buried/separate-inline' and 'mostly clear' anchors.

3 / 5

Total

14

/

20

Passed

Description

87%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.

This is a strong description: it states a concrete capability across two named surfaces, gives an explicit and varied 'Use when…' trigger list, and even includes cross-skill routing to reduce overlap. The only weaknesses are slightly narrower action coverage and a few missing natural synonyms in the trigger list.

DimensionReasoningScore

Specificity

The description names several concrete, distinct actions — 'Reframe work from output/activity language to outcome language', 'classified on the Input→Activity→Output→Outcome→Impact taxonomy', and 'pressure-testing a message before a leader sends it' — with only minor gaps in coverage, matching the 'lists several specific actions' anchor rather than the comprehensive 5.

4 / 5

Completeness

It explicitly answers both questions: what ('Reframe work from output/activity language to outcome language, on two surfaces — backlog items… and leadership asks') and when (a 'Use when…' clause with five concrete trigger scenarios), plus routing guidance to sibling skills, matching the top anchor exactly.

5 / 5

Trigger Term Quality

'Use when reviewing backlog epics in bulk, facilitating PI planning, running a value orientation audit, coaching a product owner on outcome-driven planning, or pressure-testing a message' covers natural phrasings a practitioner would actually say, but misses common synonyms and variations (e.g., user stories, OKRs, sprint planning), so it falls just short of comprehensive.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (outcome framing for backlog items and leadership asks) and actively disambiguates from adjacent skills ('use sniff-test', 'run ai-activity-to-impact first'), minimizing the chance of triggering for the wrong skill.

5 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

referenced_paths_exist

Referenced path issues: 3 missing

Warning

Total

14

/

16

Passed

Repository

yyeret/ai-impact

Path

skills/outcome-framing-coach/SKILL.md

Reviewed

Table of Contents

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