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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.

64

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

63%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-engineered process specification with excellent per-step structure, explicit data contracts, and approval checkpoints at every stage. The main costs are token weight — rhetorical padding and large reference tables inlined into SKILL.md — and the absence of failure-path guidance for steps that depend on external tools.

Suggestions

Move stable reference material out of SKILL.md into one-level-deep reference files — e.g. references/event-angle-mapping.md for the Step 3 category table and references/sensitivity-guidelines.md — keeping the body to the workflow, contracts, and checkpoint formats.

Trim motivational prose (the event-type litany, "Why this composite exists", repeated "Pure LLM reasoning — inherently tool-agnostic" tags) to cut token cost without losing executable guidance.

Add brief failure-path handling to the tool-dependent steps: what to do when a URL cannot be fetched, when zero entities pass ICP qualification, or when the contact tool returns no matches (e.g. skip, fallback, or surface to the user at the checkpoint).

DimensionReasoningScore

Conciseness

Mostly task-specific and efficient, but several sections are padded: the rhetorical event litany ("A regulation change. A product recall. A competitor acquisition…"), the "Why this composite exists" flavor text, and repeated "Pure LLM reasoning — inherently tool-agnostic" formulas could be trimmed without losing guidance.

3 / 5

Actionability

Concrete and executable for an instruction-only skill: exact search query strings, full input/output JSON contracts for every step, one-sentence angle templates with worked examples, and a fully written sample email. Falls short of 5 because several sample outputs are placeholders ("[full email]", "[New angle — data migration complexity, with a specific metric]").

4 / 5

Workflow Clarity

Steps 0–6 are clearly sequenced, each with Purpose, Input Contract, Process, Output Contract, and a Human Checkpoint approval gate, plus an Execution Summary table. Not 5 because error-recovery feedback loops are absent — failure modes like an unfetchable URL, zero ICP-qualified entities, or no contacts found are unaddressed.

4 / 5

Progressive Disclosure

Internal structure is strong (one section per step, consistent subsection layout), but no bundle files exist and all ~800 lines are inline — reference-style material like the event-category-to-urgency mapping table, the sensitivity guidelines, and the Step 0 config questionnaires are candidates for separate reference files.

3 / 5

Total

14

/

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: concrete, third-person capability statements paired with an explicit and unusually detailed auto-trigger clause using natural user phrasing. Its only weakness is intentional breadth — as a self-described catch-all for any external news signal, it overlaps with the more specific signal composites and could fire in their place.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete actions in third person — "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 using the news as the hook" — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Both "what" (evaluate ICP fit, identify connection, find contacts, draft outreach) and "when" (the AUTO-TRIGGER clause with concrete user-quoted phrases like "came across" and URL sharing) are explicitly and concretely stated, matching the top anchor.

5 / 5

Trigger Term Quality

Natural trigger language is extensive: "an article, LinkedIn post, tweet, announcement", "came across", "saw", "found", "relevance, fit, ICP match, or whether to reach out", covering synonyms and the phrasings a user would actually say. A 4 would require a few natural terms to be missing, which is not the case.

5 / 5

Distinctiveness Conflict Risk

The scope is deliberately broad — "any piece of news — … or any other public event" and "any signal evaluation request from an external source triggers this" — so news about funding, hiring, or layoffs would match both this skill and the sibling signal composites it says it complements. It is somewhat specific (news-triggered outreach) but the overlap with closely related skills is real and by design, fitting the 3 anchor rather than the minor-overlap 4 anchor.

3 / 5

Total

18

/

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 (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
Reviewed

Table of Contents

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