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arai_recent_decisions

Check recent guardrail decisions to identify repeated rule violations and avoid reattempting refused actions. Returns each firing's tool, decision, matched rules, and source file.

Instructions

Look up the most recent guardrail decisions Δ€rai has emitted in this session (or any session if session_id is omitted). Use this when you've just been denied or warned and want to check whether you've hit the same rule before β€” closes the feedback loop so you don't repeat a refused action. Returns each firing's tool, decision (deny/inject/review), the matched rule(s), and the source file the rule came from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum decisions to return (default 10, max 50).
session_idNoOptional Claude Code session id. When set, only decisions from that session are returned. Match the value Claude Code passes in hook payloads.
sinceNoOptional time window like '1h', '24h', '7d'. Defaults to the last 24 hours so stale entries don't crowd out today's.
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns tool, decision type, matched rules, and source file. It also explains the default time window and session scoping. However, it does not explicitly state whether the operation is read-only or if there are side effects, though the nature of the tool suggests it is safe.

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 three sentences with no extraneous content. It front-loads the purpose, then gives usage guidance, and finally details the return value. Every sentence adds value.

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?

Given the tool has 3 optional parameters and no output schema, the description adequately explains the purpose, usage, and return fields. It covers default behavior for parameters and mentions the return structure. It could be improved by noting result ordering (implied as most recent) or error handling, but it's still reasonably complete.

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 100%, giving a baseline of 3. The description adds meaning beyond the schema by explaining that session_id should match Claude Code hook payloads and that since defaults to 24 hours to avoid stale entries. This provides useful context not present in the raw schema.

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 looks up recent guardrail decisions, using the verb 'look up' and specifying the resource as 'guardrail decisions'. It differentiates from sibling tools like arai_add_guard (adding guards) and arai_list_guards (listing guards) by focusing on decisions, not guards themselves.

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?

The description explicitly advises when to use the tool: 'Use this when you've just been denied or warned and want to check whether you've hit the same rule before.' It provides a concrete use case and explains the benefit of closing the feedback loop.

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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