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channel-economics

Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and VP Sales doing quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led) and nobody actually knows which channel makes money after CAC, support load, partner discount, deal-velocity differences, retention differential, and overhead allocation are all loaded in. Outputs cost to serve, channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested channel-mix recommendation, and the diminishing-returns inflection (e.g., 'which channel actually makes money — direct or partner?').

64

Quality

78%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.gemini/skills/channel-economics/SKILL.md

The canonical home for this skill is channel-economics in alirezarezvani/claude-skills

SKILL.md
Quality
Evals
Security

Quality

Content

65%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 is well-structured and actionable with a clear workflow, but it lacks explicit validation/feedback loops for batch decision operations and references bundle files (scripts, references, assets) that are not present, weakening both workflow clarity and progressive disclosure.

Suggestions

Add explicit validation checkpoints to the workflow (e.g., verify the channel_data_template is complete and overhead allocation is consistent before running ROI; a validate -> fix -> retry loop for the analyzer outputs).

Ship the referenced bundle files (assets/channel_data_template.md, the three scripts/*.py, the three references/*.md) or remove the dangling references so progressive disclosure is backed by real files.

Trim repeated restatements of "the skill recommends; the human commits" and condense the forcing-question library to reduce token weight without losing the grill-discipline guidance.

DimensionReasoningScore

Conciseness

Dense and assumes competence (no explanation of CAC/LTV/MDF), with tight sections; a few repeated "skill recommends, humans commit" restatements and the seven-question library carry some redundancy that could be trimmed.

4 / 5

Actionability

Concrete executable commands throughout ("scripts/cost_to_serve_calculator.py --input channel.json --output markdown", "--profile {saas,api,...}", "--sample") and a copy-paste quick example; minor gap is the absence of an inline JSON input shape, though --sample mitigates it.

4 / 5

Workflow Clarity

Clear 5-step sequence with named scripts and outputs, but validation checkpoints and error-recovery feedback loops are largely absent for batch/decision operations, capping the score per the rubric's destructive/batch validation rule.

3 / 5

Progressive Disclosure

References to assets/, scripts/, and references/ files are clearly signaled and one level deep, but none of the referenced bundle files actually exist in the skill directory, so the intended one-level-deep navigation cannot be exercised.

3 / 5

Total

14

/

20

Passed

Description

92%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.

The description is concrete, trigger-rich, and explicitly answers both what and when with a clear audience and output set. It is a strong, well-scoped skill description with minimal conflict risk.

DimensionReasoningScore

Specificity

Names multiple concrete actions ("computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints") and concrete outputs ("channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested channel-mix recommendation"), giving comprehensive coverage.

5 / 5

Completeness

Opens with an explicit "Use when..." clause and concretely states both what it does (compute cost-to-serve, ROI, mix) and when to use it (quarterly review, mixed pipeline, nobody knows which channel is profitable), including audience and outputs.

5 / 5

Trigger Term Quality

Strong natural triggers a Head of Commercial/RevOps would say ("quarterly channel review", "channel ROI", "cost-to-serve", "channel mix", "direct vs. partner-led"), with good synonym coverage; a few natural variations are implied rather than enumerated.

4 / 5

Distinctiveness Conflict Risk

Highly distinctive niche ("direct vs. partner-led channel economics" after loading CAC, support load, partner discount, retention differential) with minimal overlap risk against adjacent finance/partnership skills.

5 / 5

Total

19

/

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 11 missing

Warning

Total

14

/

16

Passed

Repository
alirezarezvani/claude-skills
Reviewed

Table of Contents

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