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Glama

think

Escalates hard reasoning problems to a stronger model when local analysis stalls, returning read-only analysis, options, a recommendation, and open questions.

Instructions

Escalate a hard reasoning problem to a stronger model (read-only). Returns analysis, options, a recommendation and open questions.

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": {
      "problem": "<problem>"
    },
    "name": "think"
  }
}

Input Schema

NameRequiredDescriptionDefault
cwdNoRepository path
agentNo
modelNo
effortNo
problemYesGoal, constraints, what was tried
sessionNoRun group labeldefault
context_runsNoFinished run ids to pass in as context

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.3

TDQS

B3/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It does disclose that the operation is read-only and what the response contains (analysis, options, recommendation, open questions), but it says nothing about whether the call blocks or returns a run id, which matters given the session, context_runs, resume, and cancel parameters and siblings.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the action and scope, then the return shape. No filler, though the parenthetical read-only marker would read better if integrated into a single clause.

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?

Return contents are covered in lieu of an output schema, which is good, and the purpose is clear. For a 7-parameter tool with no annotations and an async-looking session/run-id surface, the missing detail on execution model and on the model/effort controls leaves the definition only minimally sufficient.

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 coverage is 57%, and four parameters (cwd, agent, model, effort) have no schema descriptions at all. The description adds no parameter meaning and never resolves the apparent tension between escalating to 'a stronger model' and exposing a user-supplied model parameter, so the key control is left ambiguous.

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?

The description states a specific verb and resource: escalate a reasoning problem to a stronger model, and the '(read-only)' tag separates it from mutating siblings such as run, execute, or merge. It does not explicitly name the nearest sibling (plan, explain, review), so the boundary is inferable rather than stated.

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?

Usage is only implied by the phrase 'a hard reasoning problem', which suggests this is the escalation path when ordinary reasoning fails. There is no explicit when-not guidance and no named alternative such as plan or explain, so an agent must guess where the threshold sits.

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