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sipyourdrink-ltd

Bernstein - Multi-agent orchestration

bernstein_task_capsule

Read and optionally verify a task's context capsule offline using the run journal and audit chain for multi-agent orchestration workflows.

Instructions

Return the worker's context capsule, optionally verified offline.

Args: task_id: The task whose capsule to read. Must be a plain identifier - path separators and traversal are refused. workdir: Project root directory (default: current directory). verify: When true, recompute the capsule offline from the run journal and audit chain and include the verdict.

Returns: JSON of the capsule projection (and, when verify is set, the offline verification result). A mock-layer fixture is reported as such and never verifies as real.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
verifyNo
task_idYes
workdirNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description discloses the optional offline verification behavior and the mock-layer fixture handling. However, with no annotations, it does not explicitly state side effects (e.g., read-only nature) or authentication requirements.

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

Conciseness4/5

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

The description is well-structured with a summary line followed by Args and Returns sections. It is concise without extraneous information, though a slightly more compact format could improve readability.

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?

Given the tool has an output schema, the description adequately explains the return value (capsule projection and optional verification result). It covers key behavioral aspects like mock-layer handling, leaving little ambiguity for a read operation.

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 description coverage is 0%, but the description adds meaningful context for each parameter: task_id must be a plain identifier (refusing path separators), workdir has a default, and verify triggers offline recomputation. This compensates for the empty schema descriptions.

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 action ('Return the worker's context capsule') and the resource ('task capsule'). It distinguishes this tool from siblings by its specific purpose of reading a capsule, opposed to running tasks or checking status.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like bernstein_status or bernstein_run. There is no mention of prerequisites or scenarios where this tool is appropriate.

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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