analyze_model_efficiency

SERVERMeridian SOURCE@meridianmcp/mcp

Low RISK CLASS

Category Read

Parameters 60 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-ajc3xc-meridian/analyze-model-efficiency.md

WHAT IT DOES

What analyze_model_efficiency does on Meridian

AI agents call analyze_model_efficiency to retrieve information from Meridian without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Parameter	Type	Required	Description
`size`	string	—	Optional explicit sprint-item size estimate (case-insensitive). Larger -> more expensive.
`files`	array	—	Alternative to file_count: the list of files touched; its length is used when file_count is omitted.
`title`	string	—	Task / sprint-item title. Scanned for cheap/expensive keyword signals.
`file_count`	integer	—	Number of files the task touches. Fewer files -> cheaper tier.
`description`	string	—	Optional longer description; also scanned for keyword signals.
`touches_resources`	array	—	Resources (DB/schema/infra/services) the task touches. May also be an integer count. More/any resources -> more expensive.

Parameters from the server's own tool schema.

RISK

Why analyze_model_efficiency is rated Low

This tool reads and analyzes task metadata (title, description, file_count, files, touches_resources, size) to produce a classification suggestion (tier: haiku|sonnet|opus). It performs no write operations, does not execute external code or queries, and does not modify any state. It is purely informational/analytical with no side effects, making it a Read category tool with low severity.

From the tool's definition Tool description states it is a 'MECHANICAL (zero-token) model-tier suggestion' that 'mirrors how the ultracode orchestration script spends zero model tokens on routing.' It 'returns a suggested tier' based on input analysis.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs analyze_model_efficiency safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Meridian, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For analyze_model_efficiency, this is the rule to start with:

analyze_model_efficiency Allowed

analyze_model_efficiency is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "analyze_model_efficiency": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Meridian, apply this rule, and every analyze_model_efficiency call is checked against it from then on.

FAQ

Questions about analyze_model_efficiency

What does the analyze_model_efficiency tool do? +

[MAINTENANCE] 0fba4cb6 — MECHANICAL (zero-token) model-tier suggestion for a task or sprint item. Deterministic, rule/heuristic classifier: NO model call, NO DB, NO network — it mirrors how the ultracode orchestration script spends zero model tokens on routing. Pass a task descriptor (any of title, description, file_count, files, touches_resources, size) and it returns a suggested tier: {tier: 'haiku'|'sonnet'|'opus', score, signals:[{signal, detail, weight}...], rationale, mode:'mechanical'}. Cheap-leaning signals (title keywords like 'typo'/'docstring'/'lint', 1 file, size 'xs'/'s') pull toward 'haiku'; expensive-leaning signals ('refactor'/'migration'/'auth', many files, touched resources, size 'l'/'xl') pull toward 'opus'. Use it to route a task to the cheapest sufficient model before spawning an executor. FOLLOW-UP (out of scope this pass): a second LLM-backed 'semantic' mode that reads the full item for a nuanced second opinion. It is categorised as a Read tool in the Meridian MCP Server, which means it retrieves data without modifying state.

What parameters does analyze_model_efficiency accept? +

analyze_model_efficiency accepts 6 parameters: size, files, title, file_count, description, touches_resources. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on analyze_model_efficiency? +

Register the Meridian MCP server in PolicyLayer and add a rule for analyze_model_efficiency: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Meridian. Nothing to install.

What risk level is analyze_model_efficiency? +

analyze_model_efficiency is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit analyze_model_efficiency? +

Yes. Add a rate_limit block to the analyze_model_efficiency rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block analyze_model_efficiency completely? +

Set action: deny in the PolicyLayer policy for analyze_model_efficiency. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides analyze_model_efficiency? +

analyze_model_efficiency is provided by the Meridian MCP server (@meridianmcp/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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