log-probe-mcp

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Update a hypothesis's status

hypothesis_update

Update a debugging hypothesis with confirmed, refuted, or inconclusive status, attach supporting log evidence, and link related execution IDs to preserve findings for later knowledge base export.

Instructions

Marks a hypothesis confirmed/refuted/inconclusive based on evidence gathered from logs, and/or links it to the execution(s) that provided that evidence. This is the durable record that knowledge_base_export later turns into a written debugging knowledge base.

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": {
      "hypothesisId": "<hypothesisId>"
    },
    "name": "hypothesis_update"
  }
}

Input Schema

Name	Required	Description
`status`	No
`evidence`	No	Concrete evidence: quote the relevant log line(s) or data.
`hypothesisId`	Yes
`relatedExecutionIds`	No	Execution IDs that provided evidence; appended, not replaced.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 31, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the tool updates status and links executions, and mentions the durable nature. However, it does not clarify whether status is overwritten or whether relatedExecutionIds are appended (the schema does), leaving some behavioral ambiguity.

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 two sentences, with the primary action in the first sentence and contextual purpose in the second. It is front-loaded, concise, and every sentence adds value without redundancy.

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 simple update tool with no output schema, the description covers the main purpose and the durable record aspect. It lacks some merge/overwrite behavior details, but these are likely evident from the schema, making it adequately complete.

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 50%, with evidence and relatedExecutionIds already described. The description adds context that evidence comes from logs and links executions, but it does not explicitly map to all parameters (hypothesisId and status are not elaborated). It partially compensates for the coverage gap.

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 specifies the action ('marks a hypothesis confirmed/refuted/inconclusive'), the resource (hypothesis), and the connection to executions. It distinguishes itself from siblings like hypothesis_create (which creates) and knowledge_base_export (which exports), making the purpose unambiguous.

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 context by stating it is 'the durable record that knowledge_base_export later turns into a written debugging knowledge base,' implying it is used after evidence gathering and before export. However, it does not explicitly state when not to use it or compare it directly to alternatives like hypothesis_create.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.