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problem-framer

The Problem Framer is the first specialist to engage on any product work at Headout. Use this skill whenever a PM has a vague idea, a half-formed brief, a Slack thread to untangle, or a gut feeling that something should be built. It transforms fuzzy inputs into a sharp, structured problem frame that every other specialist (Spec Writer, Data Analyst, Prototype Builder) can work from. Trigger this skill for inputs like: "we should improve X", "users are dropping off at Y", "can we do something about Z", "here's a thread from Atish", "I want to build a feature for...", or any product idea that hasn't yet been turned into a problem statement. Also trigger when a PM is stuck on how to frame a problem or wants a gut-check on whether they're solving the right thing. Output: A structured Problem Frame doc saved to the working folder.

82

1.97x
Quality

76%

Does it follow best practices?

Impact

87%

1.97x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./plugins/headout-pm-os/skills/problem-framer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

62%

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

This is a well-structured, highly actionable skill with excellent workflow clarity and validation checkpoints. Its main weakness is verbosity — it spends significant tokens on motivational framing, explanations of why each step matters, and repeated concepts that Claude doesn't need spelled out. The content would benefit from aggressive trimming (likely 40-50% reduction possible) while preserving all the concrete guidance, which is genuinely strong.

Suggestions

Cut all motivational/justification text (e.g., 'A bad problem frame is the most expensive mistake...', 'This matters because...', 'Write it like it matters') — Claude doesn't need persuading, just instructing.

Deduplicate repeated concepts: falsifiability is covered in Step 3e, Step 3.5, Step 4, and Common Issues — consolidate into one authoritative location.

Extract the output template and the structured critique framework (Step 3.5) into separate referenced files to reduce the main skill's token footprint and improve progressive disclosure.

Remove explanatory asides like 'Don't fire five clarifying questions — pick the most important one and ask it well' — state the rule directly: 'Ask at most ONE clarifying question.'

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~250+ lines. It includes extensive motivational framing ('A bad problem frame is the most expensive mistake...'), explains reasoning Claude already understands ('This matters because a problem framing that ignores...'), and repeats concepts across steps (e.g., falsifiability is mentioned in Step 3e, Step 3.5, Step 4, and Common Issues). Much of the philosophical justification and tone-setting could be cut without losing actionability.

1 / 3

Actionability

The skill provides highly concrete, specific guidance at every step: exact file paths to read, specific Headout funnel terminology (TOFU/BOFU, S2O, C2O, GBV), a complete output template with field-level instructions, a worked example showing input→reframe→hypothesis, and specific anti-patterns with fixes. A PM or Claude could follow this and produce a well-structured problem frame.

3 / 3

Workflow Clarity

The workflow is clearly sequenced (Steps 1→2→2.5→3→3.5→4→Output) with explicit validation checkpoints: Step 2.5 has a completion criterion ('no answer would materially change the problem direction'), Step 3.5 is a structured critique with gap/impact/recommendation format, and Step 4 is a deliberation checkpoint before output. The feedback loop in Step 3.5 ('Each gap must be resolved or explicitly acknowledged') is well-defined.

3 / 3

Progressive Disclosure

The skill references external context files appropriately (CLAUDE.md, company.md, historical-pipeline.md, active-pipeline.md), but the body itself is monolithic — all content is inline in one long file with no references to supporting documents for detailed guidance. The output template, common issues, and critique framework could be split into separate files to reduce the main skill's token footprint.

2 / 3

Total

9

/

12

Passed

Description

89%

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 skill description with excellent trigger terms and completeness. It clearly defines when to use it (fuzzy product inputs) and what it produces (structured Problem Frame doc), and it explicitly positions itself relative to other skills in the workflow. The main weakness is that the specific capabilities within the transformation process could be more concretely enumerated rather than described abstractly as 'transforms fuzzy inputs into a sharp, structured problem frame'.

Suggestions

Add 2-3 specific concrete actions the skill performs, e.g., 'identifies root causes, maps user pain points, defines measurable success criteria, and separates symptoms from underlying problems' to improve specificity.

DimensionReasoningScore

Specificity

The description names the domain (product problem framing) and describes the general action ('transforms fuzzy inputs into a sharp, structured problem frame'), but doesn't list multiple specific concrete actions. It's more about the transformation concept than enumerating discrete capabilities like 'identifies root causes, maps stakeholders, defines success metrics'.

2 / 3

Completeness

Clearly answers both 'what' (transforms fuzzy product inputs into a structured problem frame document) and 'when' (explicit trigger clause with multiple example phrases and situations like 'whenever a PM has a vague idea' or 'when a PM is stuck on how to frame a problem'). Output is also specified.

3 / 3

Trigger Term Quality

Excellent trigger term coverage with natural phrases users would actually say: 'we should improve X', 'users are dropping off at Y', 'can we do something about Z', 'I want to build a feature for...', 'vague idea', 'half-formed brief', 'Slack thread', 'gut feeling'. These are realistic PM language patterns.

3 / 3

Distinctiveness Conflict Risk

Clearly carved out niche as the 'first specialist' for pre-structured product work, explicitly distinguishing itself from downstream specialists (Spec Writer, Data Analyst, Prototype Builder). The triggers are specific to the fuzzy-input-to-problem-frame stage, making conflicts unlikely.

3 / 3

Total

11

/

12

Passed

Validation

100%

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

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
headout/pm-os-marketplace
Reviewed

Table of Contents

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