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electronics-sourcing

Guide for AI agents to source electronic components using parts-mcp — tool sequencing, decision patterns, and multi-step workflows

49

Quality

55%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./content/sourceparts/skills/electronics-sourcing/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.

This is a strong, actionable skill that provides clear tool sequencing, decision patterns, and multi-step workflows for electronics sourcing. Its main strengths are concrete tool call examples with parameters, well-defined workflow sequences with validation steps, and comprehensive coverage of failure modes. Its weaknesses are moderate verbosity (some explanatory text could be trimmed) and the monolithic structure that could benefit from splitting into overview + reference files.

Suggestions

Trim explanatory sentences that state the obvious (e.g., 'This is the core sourcing workflow' or 'Real-world sourcing often has partial results') to improve conciseness.

Consider extracting the Response Patterns section into a separate PATTERNS.md reference file, as it partially duplicates earlier workflow descriptions and adds length.

DimensionReasoningScore

Conciseness

The skill is mostly efficient but includes some unnecessary verbosity. Phrases like 'This skill teaches you how to source electronic components effectively' and explanatory sentences like 'Do not skip steps 3 and 4. A part that exists in the database may be out of stock or prohibitively expensive' explain things Claude can infer. The response patterns section partially duplicates earlier workflow descriptions. However, most content is genuinely instructive.

2 / 3

Actionability

The skill provides concrete tool calls with specific parameter examples throughout. Decision rules are explicit (e.g., '3+ specific parameters → search_by_parameters'), workflows show exact function signatures, and the BOM polling pattern includes specific field names to check. The response patterns section maps user intents to exact tool sequences.

3 / 3

Workflow Clarity

Multi-step workflows are clearly sequenced with numbered steps and explicit validation checkpoints. The BOM processing pattern includes polling logic with status checking, the manufacturing pipeline enforces DFM-before-quoting ordering, and the partial failure section provides clear error recovery patterns (attempt search → report to user). The datasheet reading strategy includes a guard against context window exhaustion.

3 / 3

Progressive Disclosure

The content is well-organized with clear section headers and logical grouping, but it's a fairly long monolithic document (~150 lines of substantive content) with no references to external files. Some sections like the detailed response patterns or cost optimization tips could be split into separate reference files. However, given no bundle files exist, the inline approach is the only option, and the sections are well-structured.

2 / 3

Total

10

/

12

Passed

Description

32%

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 identifies its domain (electronic component sourcing via parts-mcp) but reads more like a document subtitle than a functional skill description. It lacks concrete actions (e.g., search, compare, check stock), natural trigger terms users would say, and any explicit guidance on when Claude should select this skill.

Suggestions

Add an explicit 'Use when...' clause with trigger conditions, e.g., 'Use when the user asks to find, source, or compare electronic components, check part availability, or build a bill of materials.'

Replace abstract meta-language ('tool sequencing, decision patterns, multi-step workflows') with concrete actions like 'search for electronic parts, compare distributor pricing, check stock levels, find alternative components.'

Include natural trigger terms users would say, such as 'BOM,' 'component search,' 'part number lookup,' 'distributor,' 'Mouser,' 'Digi-Key,' 'availability,' and 'pricing.'

DimensionReasoningScore

Specificity

Names the domain (electronic component sourcing) and mentions some aspects like 'tool sequencing, decision patterns, and multi-step workflows,' but these are meta-descriptions of the skill's structure rather than concrete actions like 'search for components, compare prices, check availability.'

2 / 3

Completeness

Describes what the skill is about at a high level but lacks any explicit 'Use when...' clause or trigger guidance. The 'when' is entirely missing, which per the rubric should cap completeness at 2, and the 'what' is also quite vague, bringing this to a 1.

1 / 3

Trigger Term Quality

Includes relevant terms like 'electronic components,' 'parts-mcp,' and 'source,' but misses common user variations such as 'find parts,' 'component search,' 'BOM,' 'distributor,' 'Mouser,' 'Digi-Key,' 'availability,' or 'pricing.'

2 / 3

Distinctiveness Conflict Risk

The mention of 'parts-mcp' and 'electronic components' provides some distinctiveness, but 'tool sequencing, decision patterns, and multi-step workflows' is generic enough to overlap with any agent workflow guide. The niche is partially defined but not sharply delineated.

2 / 3

Total

7

/

12

Passed

Validation

81%

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

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

Total

9

/

11

Passed

Repository
andrewyng/context-hub
Reviewed

Table of Contents

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