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markmhendrickson

Neotoma

by markmhendrickson
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Create a priority-1000 correction observation to override lower-priority extracted fields. Higher-priority sources remain authoritative; equal-priority ties follow configured source-kind precedence, then deterministic recency.

Instructions

Create a priority-1000 correction observation to override lower-priority extracted fields. Higher-priority sources remain authoritative; equal-priority ties follow configured source-kind precedence, then deterministic recency. Read back the entity snapshot and field provenance before claiming the correction took effect.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldYesField name to correct
valueYesCorrected value
user_idNoOptional. Inferred from authentication if omitted.
entity_idYesEntity ID to correct
overwriteNoApply even when expected_version is stale. Ignored when it is omitted.
entity_typeYesEntity type
idempotency_keyYesRequired. Client-provided idempotency key for replay-safe corrections.
expected_versionNoOptional opaque entity_version from a current entity read. A stale token returns ERR_FIELD_VERSION_CONFLICT and writes nothing.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.25.0
    • addedInput schema / properties / expected_version
      Added value: +{
+  "description": "Optional opaque entity_version from a current entity read. A stale token returns ERR_FIELD_VERSION_CONFLICT and writes nothing.",
+  "type": "string"
+}
    • addedInput schema / properties / overwrite
      Added value: +{
+  "description": "Apply even when expected_version is stale. Ignored when it is omitted.",
+  "type": "boolean"
+}
  2. Addedv0.15.0
  3. Removedv0.14.0
  4. Addedv0.12.1
  5. Removedv0.11.0
  6. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the priority-1000 creation behavior, the precedence resolution rule (source-kind precedence, then deterministic recency), and even a verification workflow ('read back the entity snapshot and field provenance'). Gaps remain on auth/permission requirements and what a caller should do on failure, but the core write semantics are unusually well surfaced.

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?

Three tight sentences with zero waste, front-loading what is created first, then conflict resolution, then verification guidance. Every sentence adds information an agent can act on.

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 an 8-parameter mutation tool with no annotations and no output schema, the description supplies the otherwise-missing behavioral contract (priority, precedence, verification). It is nearly complete; only failure handling and permissions are left unaddressed, and the version-conflict case is already covered in the schema.

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%, including the idempotency_key, expected_version/ERR_FIELD_VERSION_CONFLICT, and overwrite semantics, so the schema already does the heavy lifting. The description adds no parameter-level detail (it doesn't explain what 'priority-1000' means as a value, nor the required entity_type/field pairing), so it sits at the documented baseline.

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?

States a specific verb and resource ('Create a priority-1000 correction observation') plus its effect ('override lower-priority extracted fields'), which is far more informative than a bare name. However, it never contrasts with the sibling 'correct_transaction', so an agent must infer which correction path applies when both are candidates.

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

Usage Guidelines3/5

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

The purpose sentence implies the usage condition (only when overriding lower-priority extracted fields, and only when higher-priority sources shouldn't win), but there is no explicit when-to-use/when-not and no mention of alternatives like correct_transaction or store. Usage is implied rather than stated.

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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