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log_search

Search the local omni-dev request log for CLI/MCP invocations and their HTTP requests, returning matching records as text. Filter by time, method, status, service, command, URL, regex, or fuzzy tokens.

Instructions

Search the local omni-dev request log — every CLI/MCP invocation and the HTTP requests it issued — and return matching records as text. Read-only. Mirrors omni-dev log (the --follow tail has no MCP form). All filters are optional and AND-ed: since/until (30m/2h, a date, or an RFC3339 timestamp), method, status (200/5xx/4xx,5xx), service, command, url, grep (regex), fuzzy/query (mini-language), id. format is oneline (default), json (verbatim NDJSON), or full; limit keeps the most recent N.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoMatch this record `id` or `invocation_id` (pulls a run and its requests).
urlNoMatch a substring of the request URL.
grepNoMatch a regular expression against the raw JSON line.
fuzzyNoFuzzy tokens (substrings of the raw line); AND-ed together.
limitNoShow at most N (most recent) matching records. Unbounded when omitted.
queryNoQuery expressions (AND/OR/NOT, `field:value`, bare tokens); AND-ed.
sinceNoLower time bound: a relative window (`30m`, `2h`, `1d`), a date (`2026-07-01`), or an RFC3339 timestamp.
untilNoUpper time bound: same forms as `since` (a relative value means that long ago). Pair with `since` for a bounded window.
formatNoOutput rendering. Defaults to `oneline`.
methodNoMatch the HTTP method (case-insensitive), e.g. `GET`.
statusNoMatch the status: exact (`200`), class (`5xx`), or list (`4xx,5xx`).
commandNoMatch the resolved command-path prefix, e.g. `jira read`.
serviceNoMatch the service tag, e.g. `jira`, `datadog`, `browser-bridge`.
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explicitly states 'Read-only', which discloses safety. It also explains the AND-logic of filters, format options, and the mirroring of CLI behavior. It does not detail rate limits or auth, but the read-only nature and local log focus partially compensate.

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?

The description is a single dense paragraph that front-loads the main purpose and key traits (read-only, CLI mirror). It efficiently lists filter options and behaviors, though it could be broken into shorter sentences for readability. 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 13 optional parameters and no output schema, the description covers the essential aspects: purpose, read-only, CLI equivalent, filter combinations, time/status formats, format choices, and limit behavior. It does not explain error cases or return value structure in detail, but the format options (oneline, json, full) and 'text' hint provide sufficient completeness.

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%, so baseline is 3. The description adds value by explaining that all filters are optional and AND-ed, providing examples of time formats (30m, 2h), status patterns (5xx, 4xx,5xx), and format options. This context goes beyond the schema's per-parameter descriptions.

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 searches the local omni-dev request log for CLI/MCP invocations and HTTP requests, returning matching records as text. It distinguishes itself from sibling tools like datadog_logs_search by specifying its scope (local) and resource (omni-dev log). The verb 'Search' and resource are specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions that the tool mirrors `omni-dev log` and notes that the `--follow` tail is not available in MCP, providing context on when to use this tool versus the CLI. It does not explicitly state when not to use it compared to other search tools, but the scope is clear enough for an agent to decide.

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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