champion-tracker

Track product champions for job changes and qualify their new companies against ICP. Takes a CSV of known champions (with LinkedIn URLs), creates a baseline snapshot via Apify enrichment, then detects when champions move to new companies. Scores new companies on a 0-4 ICP fit scale. Outputs a downloadable CSV of movers with qualification verdicts.

Quality

78%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/sales/capabilities/champion-tracker/SKILL.md

Quality

Content

82%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 concise, highly actionable, and well-structured with executable commands and clear two-phase sequencing plus a cost dry-run checkpoint. The main gaps are a missing validate→fix→retry feedback loop for the batch enrichment step and slightly less explicit navigation to the bundled script.

Suggestions

Add an explicit validation/feedback loop for the batch step, e.g., instruct to run 'check --dry-run', review cost and any unmatched profiles, fix CSV/input, then re-run without --dry-run.

Add a one-line navigation cue for the bundle, e.g., 'See scripts/champion_tracker.py --help for full CLI options' under Script Usage.

Consider trimming or merging the 'File Structure' block since the path layout is already implicit in the commands and prerequisites.

Dimension	Reasoning	Score
Conciseness	The body is lean and action-oriented with dense tables and no explanations of concepts Claude already knows; not a 5 because the 'File Structure' block and some prerequisites slightly duplicate information shown elsewhere and could be trimmed, and not a 3 because there is no noticeable padding or over-explanation.	4 / 5
Actionability	Copy-paste-ready bash commands with real script paths and flags ('python3 skills/champion-tracker/scripts/champion_tracker.py init -i champions.csv --dry-run'), a concrete output-CSV column table, and an ICP scoring table with explicit points make the guidance fully executable for the common cases.	5 / 5
Workflow Clarity	Two phases are clearly sequenced (Phase A numbered agent steps, Phase B init→check) and the batch enrichment operation has a '--dry-run' cost checkpoint plus a 'status' command; not a 5 because there is no explicit validate→fix→retry feedback loop for failed enrichment or bad CSV input, and not a 3 because validation checkpoints (dry-run) are clearly present for the costly batch step.	4 / 5
Progressive Disclosure	The SKILL.md is an organized overview that points one level deep to the real scripts/champion_tracker.py bundle file with no nested references; not a 5 because the script reference is not explicitly signaled with a 'See X for Y' navigation cue, and not a 3 because structure is good and content is appropriately split rather than inlined.	4 / 5
	Total	17 / 20 Passed

Description

75%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 specific, third-person, and clearly states what the skill does across a multi-step pipeline, with strong distinctiveness. Its main weakness is the absence of an explicit 'Use when…' trigger clause, which caps completeness at 3.

Suggestions

Add an explicit 'Use when…' clause, e.g., 'Use when you have a list of known product champions and want to detect job changes and score their new companies against ICP before re-engaging.'

Include a few natural synonyms/variants alongside 'job changes' (e.g., 'role changes', 'job moves') and spell out 'ICP' as 'ideal customer profile' once to broaden trigger coverage.

Keep the concrete action list as-is — it is comprehensive and well-scoped.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions — 'creates a baseline snapshot via Apify enrichment', 'detects when champions move', 'Scores new companies on a 0-4 ICP fit scale', 'Outputs a downloadable CSV of movers with qualification verdicts' — giving comprehensive coverage; not a 4 because the action set is broad and specific rather than having minor gaps.	5 / 5
Completeness	The 'what' is clear and detailed, but there is no 'Use when…' clause or equivalent explicit trigger guidance; per the judging guidelines a missing trigger clause caps completeness at 3, so it cannot reach 4 despite the strong 'what'.	3 / 5
Trigger Term Quality	Good keyword coverage with 'product champions', 'job changes', 'ICP', 'CSV', and 'LinkedIn' that a sales-revops user would naturally say; not a 5 because common synonyms and variations (e.g., 'job moves', 'role changes', 'ideal customer profile') are absent, and not a 3 because the natural terms present go beyond minimal relevance.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche — tracking known product champions' job changes and ICP-qualifying their new employers — with distinct triggers and minimal overlap risk against other skills; not a 4 because the niche is sharply defined rather than having minor overlap.	5 / 5
	Total	17 / 20 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/sales/capabilities/champion-tracker/SKILL.md
Commit: 2523432

Reviewed: 5 days ago

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