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langbot-mcp-ops

Operate a LangBot instance through its built-in MCP (Model Context Protocol) server. Use when an AI agent needs to manage LangBot — list/create/update/delete bots, agents, pipelines, models, knowledge bases, MCP servers, and skills — over MCP instead of raw HTTP. Covers the /mcp endpoint, API-key auth (web-UI lbk_ keys and the config.yaml global key), the tool surface, and client configuration. Triggers on "langbot mcp", "manage langbot via mcp", "langbot /mcp", "langbot mcp server".

Quality

87%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 strong, information-dense operational reference with genuinely non-obvious guidance and good error-recovery coverage. Its main weaknesses are the absence of any progressive disclosure (all domains inlined in one long file) and missing example mutation payloads and post-mutation verification steps.

Suggestions

Split specialized sections (Unified execution monitoring, LLM request diagnostics, Slack quick setup, Event processors) into files under references/ and keep one-line pointers with a brief summary in SKILL.md, so the core operations content loads without the deep detail.

Add a minimal example mutation payload (e.g., a concrete create_bot or update_pipeline tool-call body) so the "same shape as the HTTP API request body" guidance is copy-paste actionable.

Add an explicit post-mutation verification step (e.g., re-fetch the resource with get_* after update_* and confirm the changed fields) to the How-to-use workflow and destructive-operation guidance.

DimensionReasoningScore

Conciseness

The body is dense with non-obvious operational facts (401/403 semantics, config replace-not-merge behavior, rkey TTL rules) and assumes Claude's competence, but ~340 lines include run-on prose blocks (Unified execution monitoring, Event processors) that could be tightened, and the time-sensitive marker "Current tools (v1)" sits outside any deprecated/old-patterns section. Not 5 because some passages exceed what strictly earns their tokens; not 3 because there is no padding or explanation of known concepts.

4 / 5

Actionability

Concrete throughout: exact endpoint URL, auth headers, a copy-paste MCP client config JSON, a full tool table, exact HTTP routes (GET /api/v1/system/context, DELETE /api/v1/provider/providers/{uuid}?cascade=true) and named parameters. The minor gap is that mutation payloads are only described as "a JSON object matching the same shape as the corresponding HTTP API request body" with no example object, keeping it below the fully copy-paste-ready anchor.

4 / 5

Workflow Clarity

The "How to use" sequence is clear with a connectivity checkpoint (get_system_info), pre-mutation discovery is mandated, and the Slack setup flow includes an explicit poll-status/authorize/apply loop with 401/403 recovery semantics in Pitfalls. Minor gaps: no explicit post-mutation verification (e.g., re-fetch after update_*), and irreversible deletions rely on cautionary text rather than a validation checkpoint — so it does not reach anchor 5.

4 / 5

Progressive Disclosure

Section headers are clear and external docs are well signaled (docs/en/plugin/dev/permissions.mdx, dev-docs/LLM_REQUEST_POLICY.md), but there is no bundle at all: ~150 lines of specialized detail (monitoring semantics, LLM diagnostics, Slack setup, event processors) is inlined in SKILL.md where the rubric expects an overview with one-level-deep reference files. Structure is present, so it sits above anchor 2, but content that should be separate is inline.

3 / 5

Total

15

/

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.

An exemplary description: third-person voice, dense with concrete capabilities, an explicit use-when clause, and natural trigger phrases. Every dimension lands on the top anchor without verbosity or over-claiming.

DimensionReasoningScore

Specificity

The description enumerates concrete actions ("list/create/update/delete bots, agents, pipelines, models, knowledge bases, MCP servers, and skills") and concrete surface details ("the /mcp endpoint, API-key auth (web-UI lbk_ keys and the config.yaml global key)"), matching the comprehensive-coverage anchor with no vague filler.

5 / 5

Completeness

It clearly answers both "what" ("Operate a LangBot instance through its built-in MCP server") and "when" ("Use when an AI agent needs to manage LangBot... over MCP instead of raw HTTP"), reinforced with concrete trigger phrases — the anchor-5 pattern.

5 / 5

Trigger Term Quality

Explicit triggers "langbot mcp", "manage langbot via mcp", "langbot /mcp", and "langbot mcp server" are the natural phrasings for this niche, covering synonyms and the endpoint-path variant a user would actually say.

5 / 5

Distinctiveness Conflict Risk

The product-specific niche (LangBot management over MCP, explicitly contrasted with raw HTTP) and product-named triggers give it a clear lane with minimal overlap risk against other skills.

5 / 5

Total

20

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository

langbot-app/LangBot

Path

skills/skills/langbot-mcp-ops/SKILL.md

Reviewed

Table of Contents

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