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

72%

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

67%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 well-structured, highly actionable multi-source workflow with executable commands, explicit scoring criteria, and genuine troubleshooting fallbacks, backed by a real helper script. The main deductions are padded rationale sections, hard-coded years in search queries, script-path inconsistencies with the actual bundle, and the absence of explicit output-validation checkpoints.

Suggestions

Remove or compress the 'Why This Works' rationale and outreach-angle explanations to a few bullets; Claude can infer the sales logic from the scoring rubric.

Replace hard-coded years ("2026") in the WebSearch queries with a placeholder like <current-year> or instruct the agent to use the current date, per the time-sensitivity guideline.

Add an explicit validation checkpoint in Phase 3 (e.g., confirm each source's JSON output parsed and contains expected fields before consolidating, and re-run failed sources once) to earn a top workflow score.

Fix script paths to match the bundle layout (scripts/search_funding.py) and note which source scripts depend on sibling skills being installed.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient — tables, commands, and a scoring rubric — but the 'Why This Works' section spends ~10 lines justifying the funding-equals-buying-signal concept, and the outreach-angle prose restates reasoning Claude can infer. Hard-coded years in the search queries ("Series A announced this week 2026") are time-sensitive and not isolated in a deprecated/old-patterns section, which the guidelines explicitly penalize. Not a 4 because these are more than minor instances; not a 2 because the bulk is dense and actionable.	3 / 5
Actionability	Concrete, executable bash commands for each source (search_funding.py flags match the actual bundled script), exact WebSearch query strings, a parameter table, and a numeric scoring rubric make this mostly copy-paste ready. Not a 5 because the Twitter command uses unfilled placeholders (<7-days-ago>), the script paths are written as skills/funding-signal-monitor/scripts/... rather than the bundle-relative scripts/, and three of the four source commands depend on other skills' scripts that are not in this bundle.	4 / 5
Workflow Clarity	The four phases (Configure → Multi-Source Search → Consolidation & Qualification → Output) are clearly sequenced, Phase 3 provides an explicit qualification table plus a numeric scoring checkpoint, and the Troubleshooting section gives error-recovery fallbacks ('Fall back to Web Search + HN only'). Not a 5 because there is no explicit validation of intermediate outputs (e.g., verifying script JSON parsed before consolidation) and no 'only proceed when' gate; not a 3 because the dedup/qualification step and troubleshooting fallbacks function as checkpoints for this batch workflow.	4 / 5
Progressive Disclosure	Good structure: the HN search logic is properly externalized into the real bundled scripts/search_funding.py (one level deep, flags verified), and sections are clearly organized with headers and navigation-friendly tables. Not a 5 because the referenced script path doesn't match the bundle layout, three referenced scripts belong to sibling skills rather than this bundle, and material that could live in a reference file (outreach angle templates, troubleshooting) is inlined in a ~240-line body.	4 / 5
	Total	15 / 20 Passed

Description

66%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 solidly specific description that names concrete actions, sources, and filtering dimensions with good natural keywords. Its main structural flaw is the complete absence of a 'Use when...' trigger clause, which caps completeness, and it lists LinkedIn (unused in the body) while omitting Reddit (used in the body), creating a small over-claim/mismatch.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user wants to find startups that recently raised funding, build lead lists from funding announcements, or identify recently-funded companies for sales outreach.'

Include natural user phrasings as trigger terms such as 'startup raised', 'newly funded', 'venture capital', and 'lead generation from funding news' to broaden keyword coverage.

Align the source list with what the skill actually does (the body uses Reddit, not LinkedIn) to avoid over-claiming.

Dimension	Reasoning	Score
Specificity	"Aggregates signals from TechCrunch, Crunchbase (via web search), Twitter, Hacker News, and LinkedIn" and "Filters by stage, amount, and industry" list several concrete actions with named sources, matching the 'several specific actions; minor gaps' anchor. Not a 5 because the actions stay at the monitor/aggregate/filter/return level without comprehensive coverage of concrete capabilities (e.g., output format, scoring, or chaining are absent).	4 / 5
Completeness	The 'what' is clear and multi-part (monitor, aggregate, filter, return qualified companies), but there is no 'Use when...' clause or equivalent trigger guidance anywhere in the description — the rubric explicitly caps completeness at 3 for this. Not a 2 because the 'what' is far more than vague; not a 4 because 'when' is entirely absent rather than weakly implied.	3 / 5
Trigger Term Quality	Natural phrases like "funding announcements", "Series A-C", and "recently-funded companies" would match how a user asks for this, giving good keyword coverage. Not a 5 because common variations users would actually say — "startup raised", "venture capital", "investment round", "newly funded startups" — are missing.	4 / 5
Distinctiveness Conflict Risk	"Series A-C funding announcements" and "recently-funded companies ready for outreach" carve out a clear niche that is unlikely to trigger the wrong skill. Not a 5 because it sits in the crowded lead-generation space where sibling skills (contact-finder, cold-email-outreach) could overlap, and the source list (LinkedIn, Reddit) blurs slightly against generic web-monitoring skills.	4 / 5
	Total	15 / 20 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: cc3e518

Reviewed: 7 days ago

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