Decisify

review_execution_result

Evaluate solver execution logs to verify optimality, status, and feasibility, returning PASSED or FAILED with diagnostic analysis.

Instructions

Evaluates solver execution logs, solution optimality, status, and feasibility. Returns 'REVIEW_STATUS: PASSED' or 'REVIEW_STATUS: FAILED' with diagnostic analysis.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "execution_log": "<execution_log>"
    },
    "name": "review_execution_result"
  }
}

Input Schema

Name	Required	Description	Default
`execution_log`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 30, 2026

TDQS

B3.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return contract ('REVIEW_STATUS: PASSED/FAILED' with diagnostic analysis), but says nothing about whether the tool is read-only, whether it is expensive, or whether it can modify the execution state. Partial disclosure for a tool with zero annotation coverage.

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?

Two tight sentences, front-loaded with the verb and assessed dimensions, followed by the return contract. No filler or repetition.

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?

An output schema exists, so the return values need not be re-explained, and the description still summarizes them helpfully. However, with a 0%-documented required parameter and no annotations, the definition leaves the log format and the tool's side-effect profile unspecified.

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

Parameters2/5

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

Schema description coverage is 0% and the single required parameter 'execution_log' is undocumented in both schema and description. The description does not clarify the expected format of the log (raw stdout, JSON, file path), which is the key ambiguity an agent faces here.

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 ('Evaluates') and resource ('solver execution logs, solution optimality, status, and feasibility'), so the agent knows exactly what is assessed. It does not explicitly distinguish itself from the other review siblings (review_requirements, review_math_model, review_model_code), which is the only missing piece.

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?

No when-to-use guidance is given. The agent can infer it belongs after code execution in the pipeline, but the description never says it should follow execute_model_code or what condition triggers a review, nor does it name any alternative.

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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