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delimit_obs_alerts

Configure automated alerts for production thresholds such as latency and error rate by listing, creating, updating, or deleting alert rules based on metric series.

Instructions

Manage alerting rules — list, create, update, delete (experimental).

When to use: to configure ongoing alerts for production thresholds (latency, error rate, saturation, queue depth) against the same metric series visible via delimit_obs_metrics. Sub-actions: "list" inventories existing rules, "create" mints one, "update" edits, "delete" removes. When NOT to use: for one-shot metric queries (delimit_obs_metrics), log search (delimit_obs_logs), or the health rollup (delimit_obs_status). Also: do not call "create" repeatedly to retry a failed alert delivery — alerting is configuration, not delivery.

Sibling contrast: delimit_obs_metrics queries data; this configures automated thresholds against that data. Compared to cloud-provider alerting consoles, this routes through the ops bridge so the rule set is recorded in the same observability layer as the metric source.

Side effects: WRITES to the alert configuration on the ops backend for action in ("create", "update", "delete"); reads only for "list". Routes through backends.ops_bridge.obs_alerts. Marked EXPERIMENTAL — the schema for alert_rule is backend-specific and may evolve; pin tested rule shapes if depending on this in production. No license gate at this level (gating handled by the backend's own admin checks).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAlert sub-action. One of "list", "create", "update", "delete". Required.
alert_ruleNoRule definition dict (required for create/update). Backend-specific schema.
rule_idNoIdentifier for an existing rule (required for delete/update).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Despite no annotations, description discloses side effects: writes to alert config for create/update/delete, reads only for list. Also notes it is EXPERIMENTAL, backend-specific schema may evolve, routes through ops bridge, and no license gate. This provides strong behavioral context for an AI agent.

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?

Description is relatively long but well-structured: summary, when to use, when not to use, sibling contrast, side effects. Information is front-loaded. Each sentence adds value; no redundancy. Could be slightly more concise but overall efficient.

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's complexity (multiple actions, experimental status, no annotations, output schema present), the description is nearly complete. It covers purpose, alternatives, side effects, experimental nature, and schema volatility. Could mention error handling or permissions, but output schema covers return values.

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?

Input schema has 100% parameter description coverage, so baseline is 3. Description adds value by listing the valid action values (list/create/update/delete) and clarifying when alert_rule and rule_id are required, going beyond the schema's string only definition.

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?

Description clearly states it manages alerting rules with specific verbs (list, create, update, delete). It distinguishes from sibling tools like delimit_obs_metrics and delimit_obs_logs by specifying that this is for configuring ongoing alerts, not for one-shot queries or log search.

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 (configure ongoing alerts for production thresholds) and when NOT to use (one-shot queries, log search, health rollup, retrying failed deliveries). Also names alternatives: delimit_obs_metrics, delimit_obs_logs, delimit_obs_status.

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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