news-signal-outreach

End-to-end news-triggered signal composite. Takes any piece of news — an article, LinkedIn post, tweet, announcement, event, trend, regulation, product launch, acquisition, layoff, expansion, or any other public event — and evaluates whether the companies or people mentioned are ICP fits. If yes, identifies the connection between the news and your product, finds the right people to contact, and drafts personalized outreach using the news as the hook. Tool-agnostic. Accepts both company-level and person-level news triggers. AUTO-TRIGGER: Load this composite whenever a user shares a URL (LinkedIn post, article, tweet, blog post) or mentions a company/person they "came across", "saw", or "found" from any external source and asks about relevance, fit, ICP match, or whether to reach out. The user does NOT need to explicitly say "outreach" — any signal evaluation request from an external source triggers this.

Quality

92%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

85%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 a highly actionable, well-sequenced multi-step workflow with strong validation gates and concrete contracts. Its main weakness is progressive disclosure: a long monolithic file where email-framework, sensitivity, and reference material is inlined rather than split into one-level-deep bundle files.

Suggestions

Split the email-framework templates (Step 5), connection-angle mapping tables (Step 3), and sensitivity guidelines into separate reference files under references/, keeping SKILL.md as a concise overview with clearly signaled one-level-deep links.

Trim introductory prose such as 'Why this composite exists' and the repeated 'catch-all signal composite' framing to reduce token load without losing the actionable content.

Move the detailed relevant_news_categories examples and ICP config tables into a references/config-guide.md, leaving only the minimal field list inline.

Dimension	Reasoning	Score
Conciseness	Mostly efficient tables, contracts, and templates, but the ~765-line body retains trimmable prose such as 'Why this composite exists' and repeated introductory framing that could be tightened. It sits noticeably above the midpoint but is not perfectly lean.	4 / 5
Actionability	Fully executable guidance: per-step input/output contracts with named fields, concrete web-search query templates, email-framework templates with structure, and explicit hard rules (e.g., 48-72hr crisis delay). A modeler can copy-paste and execute.	5 / 5
Workflow Clarity	A clear seven-step sequence (0-6) with an explicit human-checkpoint approval gate after each step, validation-before-proceed feedback loops, and concrete timing/error-recovery guidance for sensitive scenarios.	5 / 5
Progressive Disclosure	Well-organized via headers, but it is a single ~765-line monolith with no bundle files in references/scripts/assets, and substantial content (email templates, framework selection, sensitivity tables) is inlined that would benefit from one-level-deep reference files.	3 / 5
	Total	17 / 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.

The description is concrete, trigger-rich, and explicitly answers both what the composite does and when to load it, while staying in third-person voice and carving out a distinct niche from sibling composites. It is among the strongest descriptions in the reference set.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'evaluates whether the companies or people mentioned are ICP fits', 'identifies the connection between the news and your product', 'finds the right people to contact, and drafts personalized outreach' — giving comprehensive coverage of the composite's capabilities.	5 / 5
Completeness	Explicitly answers 'what' (parse news, qualify ICP, identify connection, find contacts, draft outreach) and 'when' via a dedicated AUTO-TRIGGER clause with concrete trigger phrases, in third-person voice.	5 / 5
Trigger Term Quality	Captures the natural phrases users actually say — 'came across', 'saw', 'found', 'is this relevant', 'is this company a fit', 'should we reach out' — alongside URL-sharing and news-source variations.	5 / 5
Distinctiveness Conflict Risk	Occupies a clear niche — 'everything else' news-triggered outreach — explicitly distinguished from the structured funding/hiring/leadership composites, with distinct URL-sharing and signal-evaluation triggers.	5 / 5
	Total	20 / 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
skill_md_line_count	SKILL.md is long (804 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
Path: skills/outreach/composites/news-signal-outreach/SKILL.md
Commit: 2523432

Reviewed: 7 days ago

Table of Contents

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