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inbound-lead-qualification

Qualifies inbound leads against full ICP criteria — company size, industry, use case fit, role/seniority of the person. Checks CRM and existing customer base for duplicates and existing relationships. Outputs a scored CSV with qualification status, reasoning, and pipeline overlap flags. Tool-agnostic — works with any CRM, enrichment tool, or data source.

60

Quality

71%

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SecuritybySnyk

Low

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tessl review fix ./skills/lead-generation/composites/inbound-lead-qualification/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%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 composite workflow with a deterministic scoring model, explicit human checkpoints, and thorough edge-case handling — genuinely actionable throughout. Its main weaknesses are length-driven inline bloat (config schema and CSV spec belong in reference files) and the absence of a worked example or final output verification step.

Suggestions

Move the full ICP config JSON schema and the CSV column specification into reference files (e.g., references/config-schema.md, references/csv-spec.md), keeping only a minimal example inline in SKILL.md.

Add one worked example showing a single lead flowing through Steps 3-6 to a composite score and verdict, which would make the scoring logic concrete.

Add a final validation step in Step 7 (e.g., re-reading the CSV to confirm column completeness and verdict/score consistency) to close the workflow's feedback loop.

DimensionReasoningScore

Conciseness

The body is largely instruction-dense and assumes competence (e.g., 'a "Director" at a 10-person startup ≠ "Director" at a 10,000-person enterprise') without explaining concepts Claude already knows. It is not 5 because the ~55-line config JSON template and the CSV column enumeration partially duplicate the per-step output blocks and could be tightened. It is not 3 because unnecessary explanation is limited to isolated spots rather than a consistent pattern.

4 / 5

Actionability

The guidance is almost fully executable for an instruction-only skill: a weighted scoring table with numeric mappings ('Company Size 15%: match=100, borderline=50'), explicit verdict thresholds ('Score ≥ 75: qualified'), hard overrides, enum values, and concrete JSON output blocks plus a summary report template. It is not 5 because there is no worked input-to-output example of a scored lead, and not 3 because nothing is pseudocode or vague.

4 / 5

Workflow Clarity

A clear 7-step sequence with an architecture diagram, an explicit 'Human Checkpoint' in Step 1, a data gap report, and an 'insufficient_data if >3 dimensions unknown' rule provide real validation checkpoints for this batch operation. It is not 5 because there is no final verification step for the output CSV itself, and not 3 because checkpoints for the riskiest phase (data gaps before qualification) are explicit rather than implicit.

4 / 5

Progressive Disclosure

The content is well-sectioned but entirely monolithic: the full config schema, per-dimension qualification rubrics, scoring table, and CSV column reference are all inlined in a ~450-line SKILL.md with no bundle files to offload any of it. It is not 4 because content that clearly belongs in separate reference files (the config schema, the CSV column spec) is inline; it is not 2 because section structure is clean and navigable.

3 / 5

Total

15

/

20

Passed

Description

71%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, specific description that clearly communicates what the skill does across its full workflow with concrete inputs and outputs. Its main weakness is the absence of any explicit 'Use when' trigger clause, and it does not distinguish itself from adjacent lead-handling skills like inbound-lead-triage.

Suggestions

Add an explicit 'Use when...' clause with concrete trigger phrases (e.g., 'Use when the user says "qualify these leads", "check ICP fit", or "score my inbound"'), which would lift completeness and trigger-term quality.

Include a differentiating phrase such as 'thorough qualification step after triage — not fast-pass sorting' to reduce overlap risk with sibling skills like inbound-lead-triage.

Add one or two natural synonyms users would say, such as 'lead scoring' or 'sales-ready leads', to broaden trigger coverage.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions with comprehensive coverage — 'Qualifies inbound leads against full ICP criteria — company size, industry, use case fit, role/seniority', 'Checks CRM and existing customer base for duplicates and existing relationships', and 'Outputs a scored CSV with qualification status, reasoning, and pipeline overlap flags' — covering input, process, and output. It is not 4 because the action coverage has no significant gaps rather than minor ones.

5 / 5

Completeness

The 'what' is clearly and specifically stated across three sentences, but there is no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. It is not 2 because the 'what' is detailed rather than vague, and not 4 because 'when' is entirely implicit rather than just under-specified.

3 / 5

Trigger Term Quality

Good natural keyword coverage — 'inbound leads', 'qualification', 'scored CSV', 'CRM', 'ICP' — but common user phrasings such as 'score my leads', 'are these leads a fit', or 'sales-ready' are absent. It is not 3 because the present terms are genuinely natural rather than jargon-only, and not 5 because synonym coverage is incomplete.

4 / 5

Distinctiveness Conflict Risk

The niche is mostly distinct — inbound lead qualification with pipeline-overlap flagging is a specific trigger surface — but the description does not differentiate it from sibling skills such as 'inbound-lead-triage', leaving minor overlap risk with closely related lead-handling skills. It is not 5 for this reason, and not 3 because the described criteria and outputs are specific enough to avoid broad conflicts.

4 / 5

Total

16

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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