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valem

by io.github.vlad-public-code

Evolve spec

evolve_spec
Destructive

Apply an incremental SpecEvolution diff to a model, preserving live state. Returns the new version. Fails (isError) if the evolved spec is invalid, if expectedVersion no longer matches, or if a schema change would strand existing state. Prefer targeted diffs (upsertSchemaNodes/upsertSchemaDefs, upsertComponents, upsertConstants) over resending a whole section (newSchema/newViewDefinition/newConstants).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe model id.
evolutionYesA SpecEvolution document: newVersion/expectedVersion plus per-section upsert/remove lists. Schema tiers: upsertSchemaDefs/removeSchemaDefs (by $defs name), upsertSchemaNodes/removeSchemaNodes (by canonical data path), or newSchema (wholesale). View tiers: upsertViews/removeViews/newDefaultView, upsertComponents/removeComponents, or newViewDefinition. Constants: upsertConstants/removeConstants or newConstants.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoThe evolved model id.
versionNoThe model's new version after evolution.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

The description discloses that the tool modifies the model (destructiveHint true is consistent), preserves live state, returns the new version, and fails on invalid specs, version mismatch, or schema changes that strand existing state. This adds meaningful detail beyond the annotations, such as specific failure scenarios.

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?

The description is concise, with two well-structured sentences. The core action is front-loaded, followed by failure conditions and usage preference. No unnecessary fluff or repetition.

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 complexity of the nested evolution object, the description provides a high-level overview of its structure and tiers, which is essential for correct usage. It also mentions the return value and failure modes. While not every subfield is detailed, the description covers all critical aspects for an agent to use the tool effectively.

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?

The description of the evolution parameter explains the three tiers (schema, view, constants) and the corresponding upsert/remove operations, which is far more informative than the raw schema alone. The id parameter is self-explanatory. This enriches the parameter understanding significantly.

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 verb 'Apply', the resource 'incremental SpecEvolution diff to a model', and the key behavior of preserving live state. It also explicitly mentions the return value and failure conditions, distinguishing it from other modification tools like mutate or patch_model.

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 provides clear guidance on when to use this tool: for incremental spec evolution, and it advises preferring targeted diffs over wholesale section resets. It does not explicitly name alternatives or state when not to use it, but the provided guidance is sufficient for most decision-making.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but get_audit explicitly subsumes get_history and explain, and get_state with paths overlaps get_field, creating minor selection ambiguity. The detailed descriptions help, but an agent could still reach for the wrong getter.

Naming Consistency4/5

Naming is overwhelmingly consistent: snake_case with verb_noun structure and coherent get_/create_/delete_ clusters. Minor deviations like bare verbs (mutate, explain, restore, snapshot) and eval instead of evaluate prevent a perfect score.

Tool Count3/5

27 tools is above the comfortable range and feels heavy, especially with several overlapping audit/state getters that could be consolidated. That said, the domain is broad enough that the count is defensible, so it is heavy but not chaotic.

Completeness4/5

The tool set covers the full model lifecycle well: create, validate, test, mutate, evolve, read, delete, plus snapshot/restore, audit, blobs, views, library, and expression evaluation. Minor gaps like explicit export/import or separate view-management tools are workable around.

Resources