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Delimit Obs Logs

delimit_obs_logs

Search application and system logs across configured sources for a specific error string, trace ID, or user ID, and retrieve matching log lines within a chosen time window for incident investigation.

Instructions

Search application and system logs across configured sources (Pro).

When to use: during incident investigation when you have a symptom (error string, trace id, user id, request id) and need to find every log line mentioning it across the configured sources over a time window. The typical pattern is: delimit_obs_metrics flags a numeric anomaly, then this tool finds the offending log lines. When NOT to use: for numeric series (use delimit_obs_metrics), for the at-a-glance health rollup (delimit_obs_status), or to configure ongoing alerts (delimit_obs_alerts). Also: do not use this as a tail-follow surface — it is a windowed search, not a streaming subscription.

Sibling contrast: delimit_obs_metrics returns numeric series for the same backend; this returns text matches. Compared to grepping the local filesystem, this queries the centralised log store across services / hosts.

Side effects: read-only on the log backend and gated by require_premium — unlicensed callers receive a license payload and no query runs. On a licensed call, invokes backends.tools_infra.obs_logs which queries the backing log store; no data is written, no ledger entry, no notification. The response is routed through _with_next_steps.

Prerequisite: requires Delimit Pro. An unlicensed call returns {"error": ..., "upgrade": "https://delimit.ai/pricing"} without running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch string (backend-specific syntax). Required.
sourceNoOptional log source override. Default None.
time_rangeNoWindow like "1h", "24h", "7d". Default "1h".1h

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv4.7.9
    • addedInput schema / properties / query / description
      Added value: +"Search string (backend-specific syntax). Required."
    • addedInput schema / properties / source / description
      Added value: +"Optional log source override. Default None."
    • addedInput schema / properties / time_range / description
      Added value: +"Window like \"1h\", \"24h\", \"7d\". Default \"1h\"."
  2. First observedv0.1.0

TDQS

A4.1/5.0
Behavior1/5

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

The description explicitly states 'read-only on the log backend' and 'no data is written, no ledger entry, no notification,' but the annotations set readOnlyHint to false. This is a direct annotation contradiction, so the score must be 1 despite the otherwise strong behavioral detail.

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 long but well-structured with labeled sections: when to use, when not to use, sibling contrast, side effects, and prerequisite. Each section adds distinct information, and the core purpose is front-loaded in the first sentence.

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?

The description covers prerequisites, license-gating behavior, failure payloads, internal backend routing, side-effect profile, and use-case constraints. An output schema is present, so return-value details are not required. The only significant flaw is the annotation contradiction, which is scored separately.

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 description coverage is 100%, so the baseline is 3. The description adds useful semantic context beyond the schema by giving example query values (error string, trace id, user id, request id) and clarifying that the search happens over a time window across configured sources.

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?

States a specific verb and resource: 'Search application and system logs across configured sources (Pro).' It also explicitly contrasts itself with delimit_obs_metrics, which returns numeric series, making the tool distinguishable from many siblings.

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?

Provides a detailed 'When to use' section with concrete symptoms such as error strings, trace IDs, user IDs, and request IDs, plus a 'When NOT to use' section naming delimit_obs_metrics, delimit_obs_status, and delimit_obs_alerts. It even warns against using it as a streaming/tail-follow surface.

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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