funding-signal-monitor

Monitor web sources for Series A-C funding announcements. Aggregates signals from TechCrunch, Crunchbase (via web search), Twitter, Hacker News, and LinkedIn. Filters by stage, amount, and industry. Returns qualified recently-funded companies ready for outreach.

Quality

73%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/monitoring/composites/funding-signal-monitor/SKILL.md

Quality

Content

65%

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

The body is highly actionable with concrete commands, queries, and a scoring rubric, and the workflow is clearly sequenced across four phases. Its weaknesses are conciseness (the 'Why This Works' framing is padding), missing explicit validation checkpoints in the workflow, and a monolithic structure with little content offloaded to reference files.

Suggestions

Trim the 'Why This Works' section to one or two lines, keeping only the post-raise buying-window insight that Claude would not already infer.

Add an explicit validation checkpoint in Phase 3 (e.g., verify each candidate's amount/stage was parsed from a primary source before scoring, and flag low-confidence single-source entries) to raise workflow clarity.

Move the scoring rubric and outreach-angle templates into a references file (e.g., SCORING.md) linked from the body to improve progressive disclosure and reduce inline bulk.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with concrete tables and commands, but the 'Why This Works' section and post-raise rationale ('fresh capital, aggressive growth plans…') explain context Claude largely already knows and could be tightened; not level 3 because of this padding, not level 1 because the bulk is actionable rather than purely explanatory.	2 / 3
Actionability	Provides fully executable guidance — 'pip3 install requests', 'export APIFY_API_TOKEN=…', concrete 'python3 …/search_funding.py --stages …' invocations, explicit search-query strings, and a point-based scoring rubric — copy-paste ready; not level 2 because details are complete rather than pseudocode or partial.	3 / 3
Workflow Clarity	A clear four-phase sequence (Configuration → Multi-Source Search → Consolidation & Qualification → Output) with numbered sub-steps, but it lacks explicit validation checkpoints or validate→fix→retry loops before scoring/output; not level 3 because checkpoints are only implicit, not level 1 because the sequence is clearly laid out.	2 / 3
Progressive Disclosure	The one bundle script (scripts/search_funding.py) is real and clearly referenced, but the SKILL.md is a largely monolithic ~240-line inline doc with scoring rubrics, templates, and troubleshooting all in one file that could be split out; not level 3 because there is no overview-pointing-to-detailed-materials split, not level 1 because references are one-level-deep and signaled.	2 / 3
	Total	9 / 12 Passed

Description

82%

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 specific and distinctive with strong natural trigger terms, but it omits an explicit 'Use when…' usage clause, leaving the 'when' only implied and capping completeness. Adding a usage-trigger sentence would lift it to the top tier.

Suggestions

Append an explicit trigger clause, e.g. 'Use when sourcing recently-funded startup leads for sales outreach or when the user mentions funding announcements, Series A-C rounds, or recently-funded companies.'

Mention LinkedIn sourcing consistency: the description lists LinkedIn but the body provides no LinkedIn source command, so either drop it from the description or add the corresponding step.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Monitor web sources', 'Aggregates signals from TechCrunch, Crunchbase… Twitter, Hacker News, and LinkedIn', 'Filters by stage, amount, and industry', 'Returns qualified recently-funded companies' — matching the multi-action anchor; not level 2 because coverage is comprehensive rather than partial.	3 / 3
Completeness	Clearly answers 'what' but lacks any 'Use when…' clause or equivalent explicit trigger guidance, which caps completeness at 2 per the guidelines; not level 3 because 'when' is only implied, and not level 1 because the 'what' is explicit and specific.	2 / 3
Trigger Term Quality	Uses natural terms a user would say — 'funding announcements', 'Series A-C', 'recently-funded companies', 'outreach' — giving good coverage; not level 2 because common variations are well represented rather than merely 'some'.	3 / 3
Distinctiveness Conflict Risk	Targets a clear niche — Series A-C funding signals aggregated for outreach — with distinct triggers unlikely to fire for unrelated skills; not level 2 because the stage/amount/industry framing is too specific to broadly overlap.	3 / 3
	Total	11 / 12 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: gooseworks-ai/goose-skills
Path: skills/monitoring/composites/funding-signal-monitor/SKILL.md
Commit: 8866b2a

Reviewed: 1 day ago

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