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by hacksurvivor
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TypeScript
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Create conclusion

create_conclusion

Propose a durable, higher-signal conclusion from raw memories; approval is required before it becomes recallable.

Instructions

Propose a durable higher-signal conclusion. Approval is required by default before it can be recalled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
textYesConclusion text to save.
sourceNo
expiresAtNo
namespaceNo
evidenceIdsNoRaw memory IDs supporting this conclusion. Used for provenance and consolidation coverage.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.15
    • addedInput schema / properties / evidenceIds
      Added value: +{
+  "description": "Raw memory IDs supporting this conclusion. Used for provenance and consolidation coverage.",
+  "items": {
+    "minLength": 1,
+    "type": "string"
+  },
+  "maxItems": 100,
+  "type": "array"
+}
  2. Changed2 schema fields changedv0.1.7
    • addedInput schema / properties / expiresAt
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / namespace
      Added value: +{
+  "minLength": 1,
+  "type": "string"
+}
  3. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

Annotations indicate readOnlyHint=false, meaning this is a write operation, which the description implies with 'Propose'. The description adds that 'Approval is required by default' before recall, which is useful. However, it doesn't disclose any other behavioral traits like potential side effects, permissions, or the approval workflow mechanics, leaving gaps.

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 concise, with two sentences, and front-loads the core purpose. No wasted words, but it could add a bit more context without becoming verbose.

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

Completeness3/5

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

Given the tool's moderate complexity (6 params, some with descriptions) and no output schema, the description is minimally sufficient. It covers the core purpose and approval requirement, but lacks guidance on parameter usage and integration with other tools like approval. It's acceptable but not thorough.

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 coverage is 33%, so the description should clarify parameters. The description only mentions that the conclusion is 'higher-signal' and durable, but doesn't explain the purpose of 'tags', 'source', 'expiresAt', 'namespace', or 'evidenceIds'. With low coverage, this is a partial gap, but the schema has descriptions for 'text' and 'evidenceIds', so baseline 3 is appropriate.

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

Purpose4/5

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

The description clearly states the action ('Propose a durable higher-signal conclusion') and the resource (conclusion), distinguishing it from related tools like 'remember'. However, it doesn't explicitly differentiate from 'approve_conclusion' or 'list_conclusions' which are siblings, but its purpose is clear enough.

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?

The description implies that this tool is for creating conclusions, but it doesn't provide explicit guidance on when to use it versus alternatives like 'remember' or 'search_memory'. There's no mention of when not to use it or which sibling tools are preferable in specific contexts.

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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