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yc-batch-evaluator

Evaluate YC batch companies for investment — scrapes the YC directory, researches each company and its founders (work history, LinkedIn, website), assesses founder-company fit, and exports to Google Sheets with priority rankings. Use when asked to evaluate YC companies, research a YC batch, screen startups, or do due diligence on YC companies.

66

Quality

83%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

70%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 an exceptionally actionable, well-sequenced pipeline with genuine error-recovery handling for batch operations, but it is a long single-file monolith with repeated guidance and time-sensitive batch details, and most of its curl examples have broken JSON/shell quoting that prevents copy-paste execution.

Suggestions

Fix the curl examples so each JSON body is a single properly quoted -d argument — currently most close the quote after "path" and leave the remaining keys (e.g. "website_url") outside the string, making the commands non-executable as written.

Deduplicate guidance that appears multiple times (YC-partner filtering, batch tags vs. individual-page sectors, plain-URL formatting, rich Perplexity prompts) into one authoritative section, and move time-sensitive details like the 'Spring 2026' batch facts and default into a clearly labeled section so they don't age the whole skill.

Split the large reference material — the column layout, expected API response schemas, and Strong/Moderate/Weak assessment exemplars — into one-level-deep reference files (e.g. references/schemas.md, references/assessment-examples.md) so SKILL.md stays a lean overview.

DimensionReasoningScore

Conciseness

The body is mostly dense with non-obvious API specifics Claude could not know, but it repeats the same guidance several times (YC-partner filtering appears in 3a and Tips; batch-tags-vs-individual-sectors in Step 1, 3a, formatting rules, and Tips; the plain-URL rule and rich-Perplexity-prompt advice each appear twice), and embeds time-sensitive claims ('"Spring 2026" is a real YC batch… ~22 companies', a dated default batch) outside any deprecated/old-patterns section, which the guidelines penalize. This is more than the 'minor instances' of the level-4 anchor but well short of the severe padding of level 2.

3 / 5

Actionability

Concrete endpoints, auth headers, expected JSON response shapes, field-name variants, fallback calls, and a cost table make the guidance highly actionable. However, most curl examples are malformed as written — the -d '{…}' JSON body is closed early and subsequent keys like "website_url" sit outside any quotes (only the Apollo calls are well-formed) — so they are not copy-paste executable. All parameters and structure are present and trivially reassembled, fitting 'concrete commands with minor gaps' better than the pseudocode/missing-details anchor, but short of fully executable.

4 / 5

Workflow Clarity

A clearly numbered 5-step sequence with an explicit parallelization strategy, per-row update cadence, and real error-recovery loops for this batch operation (website 404 → 'Website not available or pre-launch', missing LinkedIn → Apollo name+company fallback, 'Skip gracefully… partial data > empty row', and a mandated re-sort step with 'Do not skip the sort'). Validation and feedback loops for batch failures are present, so the batch-operation cap does not apply, and this matches the top anchor.

5 / 5

Progressive Disclosure

No bundle files exist and the entire ~515-line skill is a single monolith: column layout tables, API response schemas, Strong/Moderate/Weak assessment exemplars, and formatting rules are all inlined with no one-level-deep references. Internal headers are clear and it is not a wall of text (so above anchor 2), but content that would fit separate reference files is inline and there is no reference navigation at all, matching anchor 3 rather than 4.

3 / 5

Total

15

/

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.

A strong description: specific, third-person, with an explicit 'Use when' trigger clause covering natural phrasings. The only weakness is that a few plausible user phrasings (sourcing, ranking, deal-flow vocabulary) are absent from the trigger list.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'scrapes the YC directory', 'researches each company and its founders (work history, LinkedIn, website)', 'assesses founder-company fit', 'exports to Google Sheets with priority rankings' — giving comprehensive coverage of the skill's pipeline. This matches the anchor for multiple specific concrete actions with comprehensive coverage, not the level below (which allows minor gaps in coverage).

5 / 5

Completeness

It clearly answers both questions: the 'what' is the concrete scrape→research→assess→export pipeline, and an explicit 'Use when asked to…' clause lists concrete trigger phrases. This matches the anchor that explicitly answers both what AND when; level 4 would require the 'when' to be less explicit.

5 / 5

Trigger Term Quality

'evaluate YC companies', 'research a YC batch', 'screen startups', and 'do due diligence on YC companies' give good natural keyword coverage with synonyms. It falls short of the top anchor because common variants users might say (e.g. 'rank YC startups', 'analyze a batch', 'startup sourcing', 'VC deal flow') are missing.

4 / 5

Distinctiveness Conflict Risk

It carves out a clear niche — YC batch due diligence with founder research and a Google Sheets deliverable — with distinct trigger phrases, so it is unlikely to fire for unrelated skills. Minimal conflict risk matches the top anchor.

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.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (515 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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