people-company-search-fiber

People, company, investor, and job search with LinkedIn data enrichment

Quality

50%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/lead-generation/capabilities/people-company-search-fiber/SKILL.md

Quality

Content

50%

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 well-structured, mostly executable endpoint reference with sensible cost guidance, but it is bloated by repeated parameter text and broken multi-line JSON in several examples, and lacks validation/cost checkpoints and any progressive-disclosure split.

Suggestions

Fix the broken JSON in the investor/people/company/job-search examples by folding searchParams inside the -d body object (e.g., -d '{"api":"fiber","path":"/v1/people-search","body":{"searchParams":{...}}}') so the commands are copy-paste ready.

Deduplicate the repeated getDetailedEducation/getDetailedWorkExperience parameter blurbs (state once and reference it) or move the full per-endpoint parameter tables into a references/ file to improve conciseness and progressive disclosure.

Add a short workflow with a cost-validation checkpoint before paginating paid searches (e.g., check pageSize cost, inspect the returned cursor/count, confirm with the user before fetching additional pages) to raise workflow clarity.

Dimension	Reasoning	Score
Conciseness	The body mostly respects Claude's intelligence (no "what is LinkedIn" filler) and is parameter/code-focused, but identical getDetailedEducation/getDetailedWorkExperience descriptions are repeated verbatim across ~6 endpoints and the entire ~360-line API reference is inlined, so it 'could be tightened' rather than earning the lean score-3 anchor.	2 / 3
Actionability	Each endpoint ships a concrete curl command with headers and example bodies, but four examples (investor-search, people-search, company-search, job-search) place their "searchParams" JSON outside the closed -d string, producing broken shell/JSON that is not copy-paste ready, matching 'some concrete guidance but incomplete' rather than fully executable score-3.	2 / 3
Workflow Clarity	A setup sequence (read credentials, export vars, instruct login if missing) is present, but there are no validation checkpoints (e.g., verify the key exported) and no cost/batch feedback loop before paginating $0.02/record searches, so per the batch-operations guideline workflow clarity is capped at 2.	2 / 3
Progressive Disclosure	Sections (Cost Reference, Setup, Capabilities, Usage, Use Cases) give real structure and no references exist to be deep-nested, but this is a ~360-line monolithic inline API reference that could live in a separate file, matching the score-2 '200 lines of API reference that could be in a separate file' example rather than the one-level-deep reference pattern.	2 / 3
	Total	8 / 12 Passed

Description

50%

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 clearly names its domain (people/company/investor/job search with LinkedIn enrichment) and uses some natural trigger terms, but it lacks an explicit "Use when..." clause and broad keyword variations, leaving every dimension at the mid anchor.

Suggestions

Add an explicit "Use when..." clause (e.g., "Use when the user wants to find people, companies, investors, or jobs, or to enrich a LinkedIn profile/company with contact details") to lift completeness and distinctiveness.

Broaden trigger-term coverage with natural variations users actually say (e.g., "lead generation", "sales prospecting", "find someone's email", "investor research", "LinkedIn lookup").

Name a few more concrete actions (e.g., "enrich profiles with emails, reverse-lookup by email, validate emails") to push specificity toward the multi-action score-3 anchor.

Dimension	Reasoning	Score
Specificity	Quotes "People, company, investor, and job search with LinkedIn data enrichment" name the domain and a couple of actions (search, enrichment), but it does not list multiple distinct concrete actions, so it sits at the 'names domain and some actions, but not comprehensive' anchor rather than the multi-action score-3 example.	2 / 3
Completeness	The description answers "what" (search + LinkedIn enrichment) but contains no "Use when..." or equivalent explicit trigger guidance, so per the rubric guideline a missing trigger clause caps completeness at 2 rather than 3.	2 / 3
Trigger Term Quality	Terms like "people", "company", "investor", and "job search" plus "LinkedIn data enrichment" are natural phrases a user might say, but coverage is thin with no common variations, matching 'some relevant keywords but missing common variations' rather than the broad score-3 set.	2 / 3
Distinctiveness Conflict Risk	"LinkedIn data enrichment" gives it a fairly clear niche, but the generic "search" framing and absence of explicit triggers mean it could still overlap with other prospecting/sales skills, matching 'somewhat specific but could still overlap' rather than the distinct-trigger score-3 example.	2 / 3
	Total	8 / 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/lead-generation/capabilities/people-company-search-fiber/SKILL.md
Commit: 8866b2a

Reviewed: 1 day ago

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