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langbot-eba-adapter-dev

Build, refactor, and test LangBot platform adapters for the Event-Based Agents architecture. Use when adding or migrating Telegram, Discord, or other messaging platform adapters to the EBA adapter layout, validating unified event/message conversion, writing live adapter probes, or using standalone plugin runtime plus Computer Use for end-to-end platform testing.

73

Quality

90%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

88%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 highly actionable with executable code, clear multi-step workflows, and explicit validation/feedback loops for destructive operations. It is efficient though long, and with no bundle files the progressive-disclosure structure is good but largely inline.

Suggestions

Consider moving the lengthy acceptance-coverage tables and component lists into a reference file (e.g. references/acceptance-coverage.md) referenced from SKILL.md to improve progressive disclosure and token efficiency.

Tighten the 'Controlling a running instance via MCP' and 'Common Pitfalls' sections into terser bullets to trim tokens without losing guidance.

Add a one-line 'Use when...' trigger reminder at the top of the body to mirror the description and reinforce invocation conditions.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's familiarity with LangBot/EBA, with concrete code and commands rather than padded concept explanations; a few sections (e.g., the MCP control overview, some pitfall prose) could be tightened, so it sits just below lean.

4 / 5

Actionability

Provides copy-paste-ready executable guidance throughout — a concrete adapter directory layout, a conversion-contract code block, exact `uv run`/`pytest`/`py_compile` commands, and a three-terminal standalone-runtime recipe covering the common cases.

5 / 5

Workflow Clarity

Multi-step processes are clearly sequenced with validation checkpoints: numbered 'Start Here' onboarding, a 9-step live probe workflow, a 'Before Finishing' checklist, `git diff --check`, and explicit destructive-operation gating ('run it last', 'behind flags').

5 / 5

Progressive Disclosure

Well-organized into clearly labeled sections with one-level-deep pointers to repo paths and sibling skills; no bundle files exist to split, and all content is inline, so it is well-structured but cannot fully demonstrate file-based progressive disclosure.

4 / 5

Total

18

/

20

Passed

Description

92%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, complete, and distinctive, explicitly covering both capabilities and trigger conditions in third person. It is a strong model description with only minor room for additional natural synonyms.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Build, refactor, and test', 'adding or migrating...adapters', 'validating unified event/message conversion', 'writing live adapter probes', 'using standalone plugin runtime plus Computer Use' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both what ('Build, refactor, and test LangBot platform adapters for the Event-Based Agents architecture') and when ('Use when adding or migrating...validating...writing live adapter probes, or using standalone plugin runtime...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Strong natural trigger terms including platform names ('Telegram, Discord'), 'messaging platform adapters', 'EBA adapter layout', 'live adapter probes', and 'Computer Use'; a few common synonyms or file-extension-style triggers are absent, keeping it just below comprehensive.

4 / 5

Distinctiveness Conflict Risk

A clear niche — LangBot EBA platform adapters tied to named platforms and specific artifacts (adapter layout, live probes, standalone runtime) — makes it unlikely to trigger for unrelated skills.

5 / 5

Total

19

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
langbot-app/LangBot
Reviewed

Table of Contents

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