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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?').

69

Quality

87%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 decision-support body: purpose, triggers, anti-triggers, a concrete five-step script workflow, a runnable example, and unusually valuable domain heuristics (retention differential, source-vs-influence attribution, consistent overhead allocation). Main weaknesses are the missing bundle files (the workflow is non-executable as shipped), the unspecified markdown-template-to-JSON input bridge, and inlined reference material with some duplicated sections.

Suggestions

Ship the referenced bundle files: SKILL.md references three scripts, three references, and one asset, but none exist in the bundle — as shipped, every workflow step and the References section is a dangling pointer.

Specify how the filled assets/channel_data_template.md becomes channel.json / roi.json / mix.json (format, fields, conversion step) so the script invocations in Steps 2-4 are reproducible.

Move the forcing-question library and the "Distinct from" section into a reference file (e.g., references/forcing_questions.md) and deduplicate them against "Do not use for" to cut SKILL.md length and repetition.

DimensionReasoningScore

Conciseness

The body is dense with domain-specific, non-obvious data ("MDF < 5:1", "A 5-point retention gap moves LTV by 30-50%", "$200k channel manager managing $4M of partner ARR is $50... per $1k ARR") rather than concepts Claude already knows. Minor trimmable redundancy keeps it at anchor 4: "Distinct from" re-covers the same six skills as "Do not use for", and the human-decides point is stated three times ("It does not pick the strategy — humans do", "The skill recommends; the human commits", "never an automatic resource reallocation").

4 / 5

Actionability

Commands are concrete and specific ("scripts/cost_to_serve_calculator.py --input channel.json --output markdown", "--profile {saas,api,enterprise-software,marketplace,hardware}", a runnable Quick example with --sample). Anchor 4 rather than 5 because of a minor gap: Step 1 fills a markdown template (assets/channel_data_template.md) while the scripts consume channel.json / roi.json / mix.json, and how to bridge the template to those input files is never specified.

4 / 5

Workflow Clarity

A clear five-step sequence names the script, inputs, and outputs at each step, with built-in validation ("Flags double-counting and surfaces hidden costs", "The script validates that overhead % is consistent across channels") and sequencing discipline ("Lock 1-3 before opening 4-7"). Not anchor 5 because there is no explicit feedback loop — nothing says what to do when the calculator flags double-counting or inconsistent allocation before running the next script.

4 / 5

Progressive Disclosure

The body itself is well-sectioned and its references are clearly signaled one level deep ("references/channel_economics_canon.md — Skok, Bessemer State of the Cloud, Tunguz..."), but the bundle contains none of the seven referenced files — no scripts/, references/, or assets/ directories exist — so the promised navigation targets are absent as shipped. Additionally, reference-grade material (canon citations, the ~30-line forcing-question library, and the "Distinct from" section duplicating "Do not use for") is inlined in the ~130-line SKILL.md. This matches anchor 3 ("could be better organized; content that should be separate is inline") better than anchor 4.

3 / 5

Total

15

/

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: it explicitly states what the skill computes (cost-to-serve, three-lens ROI, constrained mix) and when to use it (quarterly channel review with mixed pipeline), with concrete trigger phrases, named audience, specific outputs, and a quoted user question. It is long but dense — every clause carries information rather than padding.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions with comprehensive coverage: "computing fully-loaded cost-to-serve per channel", "channel ROI with cash / LTV / marginal lenses", "optimal channel mix subject to constraints", and explicit outputs ("channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT)", "sensitivity-tested channel-mix recommendation", "diminishing-returns inflection"). Inputs, lenses, outputs, and verdict vocabulary are all named, matching the anchor-5 example's comprehensiveness rather than anchor 4's "minor gaps in coverage".

5 / 5

Completeness

Both questions are answered explicitly: the what ("computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints") and the when ("Use when reviewing or rebalancing direct vs. partner-led channel economics... quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led)") with concrete trigger phrases and a named audience. Clearly the anchor-5 pattern, well above anchor 4's "'when' could be more explicit".

5 / 5

Trigger Term Quality

Natural user phrasings are comprehensively covered, including synonyms and a literal user-voice quote: "quarterly channel review", "which channel makes money", "cost to serve", "channel mix", "direct vs. partner-led", "CAC", "partner discount", "retention differential", "overhead allocation", and the embedded question "which channel actually makes money — direct or partner?". This exceeds anchor 4 ("a few natural terms missing") — the terms users would actually say are present verbatim.

5 / 5

Distinctiveness Conflict Risk

"direct vs. partner-led channel economics" plus the specific verdict vocabulary (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT) carves a clear niche that is distinguishable from adjacent skills like pricing design, deal-desk approval, or partner-program structure. Minimal overlap risk — matches anchor 5 ("clear niche with distinct triggers; minimal conflict risk").

5 / 5

Total

20

/

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

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

Path

.gemini/skills/channel-economics/SKILL.md

Reviewed

Table of Contents

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