FlowState Hosted

manage_rules

A project's hard rules: short never/always rules from the user, shown first in every brief and never cut. add: when the user states one (one sentence, max 300 chars; 25 rules, 2,000 chars in total); it waits in the review queue until the user approves it themselves (on their review page; no app can). list: active rules. remove: ONLY when the user asks in this chat; quote them in user_request; it waits like add; the rule is kept as removed. Preferences and lessons go in log_work. Requires project. Returns the rule or {rules}.

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": {
      "action": "<action>",
      "project": "<project>"
    },
    "name": "manage_rules"
  }
}

Input Schema

Name	Required	Description
`rule`	No	add: the rule, one short sentence.
`model`	No	Model name if known. Never guess.
`action`	Yes	The operation; see the tool description.
`project`	Yes	Project name or id. Required.
`rule_id`	No	remove: the rule's id (R<id> in the brief).
`user_request`	No	remove (required): the user's own words asking to remove it.
`include_removed`	No	list: also removed rules.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 7, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Goes well beyond the annotations by disclosing the approval workflow: additions and removals sit in a review queue until the user approves them themselves on their review page, and no app can approve. It also states that removal is soft ('the rule is kept as removed'), which is consistent with destructiveHint=false but adds the concrete consequence the annotation only hints at.

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?

Front-loaded with the resource definition, then action-keyed clauses and the return shape. Every sentence carries information, but the telegraphic semicolon chains and back-references ('it waits like add') make it denser than necessary for fast parsing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter, three-action mutation tool with no output schema, it covers the approval prerequisite, quota limits, soft-delete semantics, the cross-chat restriction on removal, and the return value ('the rule or {rules}'). Nothing an agent needs in order to call it correctly is missing.

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

Parameters4/5

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

Schema coverage is already 100%, yet the description still adds meaning: one-sentence/300-char rule limit, 25-rule/2,000-char caps, and that user_request must quote the user's own words for a removal. Minor gap: it doesn't explain include_removed or model beyond what the schema says, so it is not fully additive.

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 names the resource (a project's hard rules: short never/always rules shown first in every brief) and enumerates the three operations (add, list, remove) with what each does. It also explicitly routes non-rules content elsewhere ('Preferences and lessons go in log_work'), so an agent can distinguish it from the closest sibling.

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?

Gives explicit when-to-use per action: add when the user states a rule, remove ONLY when the user asks in this chat, list for active rules. It also names the alternative destination for related-but-different content (log_work), which is strong sibling routing.

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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