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mattermost-test-data

Backfill realistic test data into a Mattermost server using the Mattermost MCP tools. Creates users, teams, channels, and natural conversations. Use when the user asks to populate a Mattermost instance, create test data, set up a demo environment, seed conversations, or backfill a Mattermost server. Also provides guidance on reading, searching, and interacting with Mattermost via MCP tools.

68

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

65%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-structured, actionable skill body with concrete tool references and a clear dependency-ordered workflow. Its main weaknesses are the absence of validation/verification checkpoints for a batch backfill operation and no progressive disclosure into separate reference files.

Suggestions

Add explicit validation checkpoints between batch steps — e.g., after creating users/channels, verify the returned IDs are non-empty and retry on failure before proceeding to the next step.

Split the tool API tables and the detailed conversation-template patterns into a references/ file (e.g., TOOL_REFERENCE.md and CONVERSATION_PATTERNS.md), keeping SKILL.md as a lean overview with one-level-deep links.

Tighten the Conversation Quality Guidelines and Tips sections by merging overlapping bullets to reduce token load while preserving the skill-specific realism guidance.

DimensionReasoningScore

Conciseness

Mostly efficient with tables and code blocks; the realism tips and persona guidance are skill-specific and earn their place, though a few sections (e.g., the four conversation-template patterns) could be trimmed slightly. Not a 5 because there is minor padding that assumes less of Claude than necessary.

4 / 5

Actionability

Tool tables list concrete parameters and the workflow gives executable call signatures with saved IDs, plus a concrete minimal-setup example. Not a 5 because the conversation templates are abstract patterns rather than copy-paste-ready calls.

4 / 5

Workflow Clarity

A clear 7-step sequence with dependency ordering ('Follow this order to avoid missing dependencies'), but this is a batch operation (many user/channel/post creates) with no explicit validation or verification checkpoints or error-recovery loops, so per the batch-operation cap it cannot exceed 3.

3 / 5

Progressive Disclosure

Well-organized with clear section headers, but all ~200 lines live in a single SKILL.md with no bundle files; the tool API tables and detailed conversation templates are reference-like material that could be split into separate files but is inlined.

3 / 5

Total

14

/

20

Passed

Description

100%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, third-person description that concretely states capabilities and provides explicit, natural trigger phrases with good synonym coverage. It clearly answers both what the skill does and when to use it, with minimal conflict risk.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Creates users, teams, channels, and natural conversations' plus 'reading, searching, and interacting with Mattermost via MCP tools' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both what ('Backfill realistic test data... Creates users, teams, channels, and natural conversations') and when ('Use when the user asks to populate...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

The 'Use when' clause covers natural synonyms users would say — 'populate a Mattermost instance, create test data, set up a demo environment, seed conversations, or backfill a Mattermost server' — with strong synonym coverage (populate/seed/backfill).

5 / 5

Distinctiveness Conflict Risk

Scoped tightly to Mattermost test-data backfill with Mattermost-specific triggers, giving it a clear niche with minimal overlap risk against other skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mattermost/mattermost-ai-marketplace
Reviewed

Table of Contents

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