tam-sam-som-calculator

Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats. Use when sizing a market for a product idea, business case, or executive review.

Quality

75%

Does it follow best practices?

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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 highly actionable, well-sequenced interactive skill with an executable helper script, a concrete bottom-up research recipe, and a usable output template. Its weaknesses are concentrated conciseness padding (framework definitions Claude already knows) and two dangling file references that undermine progressive disclosure.

Suggestions

Trim the "Key Concepts" section to non-obvious domain guidance only (the bottom-up recipe, Fact/Inference/Assumption labeling, capture-rate trick) and drop the TAM/SAM/SOM term definitions, "Why This Works", and anti-patterns that restate known concepts; also remove the Purpose paragraph that duplicates the frontmatter intent.

Resolve the broken references by creating `template.md` and `examples/sample.md` (or removing the pointers) — currently "Use `template.md` for the full fill-in structure" and "See `examples/sample.md`" point to files that don't exist, while the output template is inlined in the body.

Add an explicit validate-and-revise loop to the main interactive flow (e.g., "if TAM disagrees with third-party reports by >2x, revisit the population or ARPU assumption and recompute") rather than only posing validation questions to the user.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient, but the "Key Concepts" section defines TAM/SAM/SOM and explains "Why This Works" / anti-patterns that Claude already knows, and the Purpose paragraph duplicates the frontmatter intent verbatim — several padded sections that could be trimmed.	3 / 5
Actionability	It provides a copy-paste-ready, verified-executable helper command ("python3 scripts/market-sizing.py --population 5400000 --arpu 1000 --sam-share 30% --som-share 10%"), a concrete bottom-up recipe with named sources, a fill-in output template, and enumerated questions with cited data covering the common cases.	5 / 5
Workflow Clarity	A clear Step 0 → Questions 1-4 → Output sequence is present with a validation checklist and Mode 3's "validate against two independent analyst reports" checkpoint, but the main interactive flow lacks an explicit validate→fix→retry feedback loop, leaving a minor validation gap.	4 / 5
Progressive Disclosure	Section structure is reasonable and the helper script reference resolves to a real file, but the body references `template.md` and `examples/sample.md` which do not exist in the bundle, and the ~90-line output template is inlined where `template.md` is said to live — references are signaled but broken, and content that should be separate is inline.	3 / 5
	Total	15 / 20 Passed

Description

78%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.

A strong, third-person description that clearly states both capability and trigger conditions with concrete PM-facing keywords. The main gap is specificity — it describes one composite calculation rather than several distinct actions — and a few missing synonyms would round out trigger coverage.

Dimension	Reasoning	Score
Specificity	"Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats" names the domain and one concrete action (one verb over three metrics), with output qualifiers rather than several distinct actions — matching the 1-2 concrete actions anchor, short of the "several specific actions" bar.	3 / 5
Completeness	It explicitly answers both what ("Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats") and when ("Use when sizing a market for a product idea, business case, or executive review") with concrete trigger phrases, matching the top anchor.	5 / 5
Trigger Term Quality	Natural PM keywords are present ("sizing a market", "TAM, SAM, and SOM", "product idea", "business case", "executive review"), but common synonyms like "market size", "addressable market", or "market opportunity" are missing, so coverage is good rather than comprehensive.	4 / 5
Distinctiveness Conflict Risk	TAM/SAM/SOM market sizing is a clear niche with a distinct primary trigger ("sizing a market"), but the secondary triggers "business case" and "executive review" are broad enough to overlap with other exec-facing skills, leaving minor conflict risk.	4 / 5
	Total	16 / 20 Passed

Validation

87%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
relative_links	Relative link issues: 3 suspicious	Warning

	Total	14 / 16 Passed

Repository: deanpeters/Product-Manager-Skills
Path: skills/tam-sam-som-calculator/SKILL.md
Commit: a03af68

Reviewed: 11 days ago

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