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leadership-change-outreach

End-to-end leadership change signal composite. Takes any set of companies, detects recent leadership changes (new VP+, C-suite hires and promotions), evaluates relevance to your product, and drafts personalized outreach. Uses Apollo People Search (free) for fast detection + Apollo Enrichment (1 credit/person) for employment history, start dates, LinkedIn URLs, and verified emails.

58

Quality

68%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/outreach/composites/leadership-change-outreach/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

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 and clearly sequenced with strong validation checkpoints, but it is verbose for a single-file skill and does not split large reference material into bundle files. Tightening or extracting the title list, config tables, and sample mockups would improve token efficiency and progressive disclosure.

Suggestions

Extract the large reusable material — the VP+ title list, the config questionnaires, and the email framework tables — into reference bundle files (e.g. references/titles.py, references/config.md) and link them one level deep to improve progressive disclosure.

Trim the illustrative human-checkpoint mockups and the Step 4 sample email block to compact templates rather than fully written-out example tables and emails.

Remove or condense the 'Key Difference from Other Signal Composites' section, since the same point is already implicit in the Step 3 description.

DimensionReasoningScore

Conciseness

It avoids explaining concepts Claude already knows and carries real signal density, but at ~690 lines it includes padding that could be tightened — the 30-line title list, full config questionnaires, elaborated human-checkpoint mockups, sample email blocks, and a 'Key Difference' section that restates the flow — fitting the score-2 anchor of mostly efficient but could be tightened.

2 / 3

Actionability

Provides fully executable guidance — exact `apollo_client.search_people()` filter dicts, the complete `is_valid_gtm_leader()` function, the `people/match` URL/payload, employment-history parsing code, exact field names, and concrete input/output contracts — matching the score-3 anchor of copy-paste-ready executable code.

3 / 3

Workflow Clarity

Steps 0–5 are clearly sequenced with per-step input/output contracts and explicit Human Checkpoint validation gates after each step ('Proceed with relevance evaluation? (Y/n)', 'Approve before we draft outreach?'), plus feedback loops (rate-limit retry, credit tracking), matching the score-3 anchor of clear sequence with explicit validation and error-recovery loops.

3 / 3

Progressive Disclosure

No bundle files exist, so this is a single ~690-line SKILL.md; it is well-sectioned with clear headers and per-step contracts, but content that could be split (title list, config tables, email frameworks) is inline, matching the score-2 anchor of some structure but content that should be separate is inline.

2 / 3

Total

10

/

12

Passed

Description

60%

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 concrete about capabilities and the Apollo mechanics, but it lacks an explicit "Use when..." trigger clause and natural trigger-term coverage is incomplete, which caps completeness and trigger quality. It is reasonably distinct but overlaps with related signal composites.

Suggestions

Add an explicit 'Use when...' clause naming natural user triggers, e.g. 'Use when a user asks to find companies with recent executive hires, new VP/C-suite leaders, or wants leadership-change outreach.'

Broaden trigger terms to cover natural variations users actually say, such as 'new executive hires', 'exec hires', 'leadership transitions', and 'leadership signal'.

Sharpen distinctiveness by contrasting the trigger with sibling composites (e.g. 'Use for leadership/person changes; use funding-signal-outreach for funding events').

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions — "detects recent leadership changes", "evaluates relevance to your product", "drafts personalized outreach", plus named Apollo APIs with the exact fields they return (employment history, start dates, LinkedIn URLs, verified emails) — matching the score-3 anchor.

3 / 3

Completeness

It clearly answers "what" (detects, evaluates, drafts) but has no explicit "Use when..." trigger clause; per the judging guidelines a missing explicit trigger caps completeness at 2.

2 / 3

Trigger Term Quality

Includes relevant terms a user might say ("leadership changes", "new VP+", "C-suite hires", "outreach") but misses common natural variations such as "new executive hires", "exec hires", or "leadership transitions", fitting the score-2 anchor of some keywords but missing common variations.

2 / 3

Distinctiveness Conflict Risk

The leadership-change-via-Apollo niche is fairly distinct, but it overlaps with sibling signal composites (funding-signal-outreach, hiring) and cold-email-outreach referenced in the body, matching the score-2 anchor of somewhat specific but able to overlap with similar skills.

2 / 3

Total

9

/

12

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (722 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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