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agent-lsp

agent-lsp

by blackwell-systems
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Hybrid

evaluate_session

Compare current diagnostics against baselines to measure errors introduced, resolved, and net delta after a simulated edit. Get confidence levels to assess impact before committing.

Instructions

Evaluate a simulation session by comparing current diagnostics against baselines. Returns errors introduced, errors resolved, net delta, and confidence (high for file scope, eventual for workspace). Use after simulate_edit to assess impact before committing.

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": {
      "session_id": "<session_id>"
    },
    "name": "evaluate_session"
  }
}

Input Schema

NameRequiredDescriptionDefault
scopeNo
session_idYes
timeout_msNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.16.0
  2. Removedv0.15.0
  3. Addedv0.11.1
  4. Removedv0.10.0
  5. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries full behavioral burden. It describes return values and confidence levels (high for file scope, eventual for workspace). However, it does not mention side effects, idempotency, or whether it mutates state, leaving some behavioral gaps.

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 sentences: first defines purpose and output, second gives usage guidance. Extremely concise, front-loaded, and every word adds value.

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?

The description covers purpose, usage, and return values adequately given no output schema. However, parameter details are missing, which is a gap for a tool with 3 parameters and no schema description. It is minimally complete but not thorough.

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 has 3 parameters with 0% description coverage in the schema. The description mentions file vs workspace scope in the context of confidence but does not explicitly document the 'scope' parameter or explain 'session_id' or 'timeout_ms'. Parameter semantics are underdeveloped.

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 tool's purpose: evaluating a simulation session by comparing diagnostics against baselines. It lists specific outputs (errors introduced, errors resolved, net delta, confidence) which distinguishes it from siblings like simulate_edit or simulate_chain.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'Use after simulate_edit to assess impact before committing.' This provides clear context and distinguishes from other tools in the session lifecycle.

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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