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dialogbrain

by io.github.saloprj
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prompts_blocks_preview

Read-onlyIdempotent

Assemble an agent's system prompt through the REAL builder and return it block by block with attribution (id, kind, cache phase, token estimate), the cached-prefix/dynamic-suffix split, and any ignored stale overrides or missing translations. Byte-equality with the production assembly is verified — the preview cannot lie. Use after prompts.blocks_update to see the effect.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesAgent whose prompt to assemble.
thread_idNoOptional thread to load real situation/history context from.
in_workspaceNoRun this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / in_workspace
      Added value: +{
+  "description": "Run this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.",
+  "type": "integer"
+}
  2. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the bar is lower, yet the description adds real value: 'Byte-equality with the production assembly is verified — the preview cannot lie' declares fidelity guarantees beyond the annotations, and it notes ignored stale overrides/missing translations in the output.

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?

Two dense sentences, front-loaded with the core action and followed by the usage trigger. Every clause carries information, though the first sentence is packed with several enumerated items that could be tightened.

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?

For a read-only preview with full schema coverage and no output schema, the description compensates by describing the return structure (per-block attribution, cached/dynamic split, ignored overrides). The behavioral and output picture is essentially complete for correct invocation.

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

Parameters3/5

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

Schema description coverage is 100%, so agent_id, thread_id and in_workspace are already documented in the schema. The description adds no parameter-level syntax or format detail beyond what structured data provides, so the baseline 3 applies.

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?

States a specific verb (assemble/preview) and resource (an agent's system prompt) and details the exact return shape — block-by-block attribution, cache-phase split, ignored overrides. This is far more specific than the sibling prompts_blocks_get and lets an agent distinguish the preview function without opening the schema.

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?

Explicitly says 'Use after prompts.blocks_update to see the effect,' giving a concrete trigger and pointing at the related sibling workflow. It stops short of naming any when-not conditions or contrasting with prompts_blocks_get, so it is clear context without full exclusions.

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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