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sipyourdrink-ltd

Bernstein - Multi-agent orchestration

bernstein_post_message

Post a signed journal entry to a task's mailbox, appending a verifiable progress record without changing task fields.

Instructions

Post a message to a task's mailbox as a signed journal entry.

Wraps the worker mailbox: the message is DLP-redacted, HMAC-chained onto the mailbox journal, Ed25519-signed, and mirrored to the audit chain (task.mailbox_message) before returning. The result IS the signed journal entry - a worker holds a progress record it can verify offline against the same chain bernstein audit verify walks, not a bare status string. This tool never changes a task's fields; it appends to the task's mailbox.

Args: task_id: The task the message is addressed to. body: The message body (<= 4096 bytes). sender: The posting worker's identity. kind: Typed message kind - one of finding / artefact_ref / question. sender_card_fingerprint: sha256: fingerprint of the sender's agent card key.

Returns: JSON of the signed mailbox journal entry (seq, prev_entry_hash, entry_hash, signature, signer_public_key_pem, body_hash, ...).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
kindNo
senderYes
task_idYes
sender_card_fingerprintNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: DLP-redaction, HMAC-chaining, Ed25519-signing, mirroring to audit chain, and that the result is a signed journal entry. It explicitly states that task fields are never modified.

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 paragraphs and an Args/Returns section, but it is somewhat verbose. Every sentence adds value, but some technical details could be streamlined without loss of clarity.

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

Completeness5/5

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

For a tool with 5 parameters (3 required) and an output schema, the description covers all aspects: parameter details, return format (JSON with specific fields), and behavioral constraints (never changes task fields). It is complete given the tool's complexity.

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

Parameters5/5

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

Since the input schema has 0% description coverage, the description provides complete parameter documentation: types, constraints (e.g., body max 4096 bytes), enums for 'kind', and optionality for 'sender_card_fingerprint'. This adds significant meaning beyond the bare schema.

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 begins with 'Post a message to a task's mailbox as a signed journal entry,' which is a specific verb+resource combination. It clearly distinguishes from siblings like 'bernstein_post_artifact' by focusing on messages and mailboxes.

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

Usage Guidelines4/5

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

The description explains what the tool does and explicitly states what it does not do ('never changes a task's fields; it appends to the task's mailbox'). It implies usage for posting messages only but lacks direct comparison with sibling tools for alternative selection.

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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