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ai-dev-jobs-mcp

Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP

57

Quality

66%

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tessl review fix ./plugins/antigravity-awesome-skills/skills/ai-dev-jobs-mcp/SKILL.md

The canonical home for this skill is ai-dev-jobs-mcp in popey/claude-code-skills

SKILL.md
Quality
Evals
Security

Quality

Content

50%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a competent MCP tool reference skill that clearly documents available tools and their parameters, with a usable configuration block. However, it suffers from moderate verbosity (time-sensitive stats in the overview, redundant examples that restate tool descriptions), lacks concrete output schemas or error handling guidance, and could benefit from tighter organization. The examples add little value beyond what the tool descriptions already communicate.

Suggestions

Remove or move the time-sensitive live stats from the overview (8,405 roles, $213,500 median) to avoid stale data; instead instruct the agent to call get_stats for current numbers.

Add example response schemas or sample output JSON for at least the most-used tools (search_jobs, get_job) so Claude knows what to expect and how to present results.

Trim the Examples section significantly—it largely restates the tool descriptions. Keep 1-2 examples that show multi-tool workflows (e.g., list_companies → search_jobs → get_job pipeline).

Add brief error handling guidance: what to do when search returns no results, when a job ID is invalid, or when salary data is unavailable.

DimensionReasoningScore

Conciseness

The skill includes some unnecessary verbosity: the overview paragraph with specific live stats (which are time-sensitive and will become stale), explanations of when to use the skill that Claude could infer, and the examples section largely restates what the tool descriptions already convey. The tool listing itself is reasonably lean.

2 / 3

Actionability

Tool invocations are shown with example parameters, which is helpful, but they are not fully executable code—they're pseudocode-style function calls without language context. The MCP configuration JSON is concrete and copy-paste ready, but the examples section describes what the agent 'will do' rather than showing actual output schemas or response formats.

2 / 3

Workflow Clarity

The Best Practices section provides a reasonable suggested workflow (e.g., use list_companies then search_jobs, use get_stats for context first), but there are no explicit multi-step sequences with validation checkpoints. For a tool-calling skill this is somewhat acceptable, but the skill doesn't address error handling, empty results, or what to do when tools return unexpected data.

2 / 3

Progressive Disclosure

The content is well-structured with clear sections (Overview, Tools, Examples, Best Practices, Limitations), but it's somewhat monolithic at ~130 lines. The examples section could be trimmed or moved to a separate file. There are no bundle files, and the related skills references are present but minimal. For a standalone skill of this size, the organization is adequate but not optimal.

2 / 3

Total

8

/

12

Passed

Description

82%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong description with excellent specificity and distinctiveness, clearly naming the domain (AI/ML jobs), concrete actions (search, inspect, match, view stats), and the specific tool (AI Dev Jobs MCP). The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill over others.

Suggestions

Add a 'Use when...' clause such as 'Use when the user asks about AI jobs, ML careers, developer job listings, tech salary data, or wants to search for positions at AI companies.'

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: search jobs, inspect listings and employers, match roles, view salary and market stats. Also specifies the domain (AI and ML jobs) and scale (8,400+ jobs, 489 companies).

3 / 3

Completeness

Clearly answers 'what does this do' with specific actions and domain, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The when is only implied by the nature of the actions described.

2 / 3

Trigger Term Quality

Includes strong natural keywords users would say: 'AI jobs', 'ML jobs', 'job search', 'salary', 'market stats', 'companies', 'listings', 'roles'. These are terms users would naturally use when looking for AI/ML employment opportunities.

3 / 3

Distinctiveness Conflict Risk

Very distinct niche: AI/ML job searching via a specific MCP tool (AI Dev Jobs MCP). The combination of job search + AI/ML domain + specific tool name makes it highly unlikely to conflict with other skills.

3 / 3

Total

11

/

12

Passed

Validation

90%

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

Validation — 10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
popey/claude-code-skills
Reviewed

Table of Contents

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