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bridge_health

Checks the whole delegation chain: credential file, serve stability, auth, provider models, and skills. Deep mode runs a real MCP call on the cheapest model to confirm end-to-end readiness.

Instructions

Check the whole delegation chain in one call: credential file readable, serve up and STABLE (two spaced reads, so a dying instance cannot pass), auth enforced, provider models present, skills valid. With deep=true also runs a REAL MCP call through a disposable delegation on the cheapest model, then deletes that session. Run it with deep=true before a batch of delegations and whenever the environment smells broken - it is the manual liveness test turned into code. Do not run deep=true in a loop: it spends tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNotrue = also run a real MCP call through a throwaway session on the cheapest model
modelNoModel for the deep probe (alias or "provider/model"). Defaults to "cheapModel" from bridge.config.json.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite having no annotations, the description thoroughly discloses behavior: the two spaced reads to prevent dying instances from passing, the deep mode running a real MCP call through a disposable delegation and deleting the session, and the token cost warning. This goes beyond what structured data provides.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence earns its place: it lists the checks, explains deep mode, gives usage guidance, and warns about tokens. The structure is logical and front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers behavior, parameters, and usage thoroughly, which is impressive without annotations or an output schema. The only gap is that it doesn't explicitly describe the return value or response format, which would be helpful for an agent interpreting the health check results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters. The description adds semantic depth by explaining that deep=true triggers a real MCP call on the cheapest model and that the model parameter controls the probe model, tying it to the configuration's cheapModel default.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check the whole delegation chain in one call' and enumerates the specific checks performed (credential file, server stability, auth, provider models, skills). It distinguishes itself from sibling task-management tools by presenting a distinct health-check role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit usage guidance is provided: 'Run it with deep=true before a batch of delegations and whenever the environment smells broken' and 'Do not run deep=true in a loop: it spends tokens.' This tells the agent when and when not to use the tool, fulfilling the dimension fully.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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