elog-mcp

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elog_search

Find electronic logbook entries by full-text regex, attribute filters, or date range. Retrieve matching entries with excerpts, metadata, and attachments to locate records quickly.

Instructions

Search logbook entries by full text, attributes, and/or date.

Args: text: Regular expression matched against entry message bodies. Use ^…$ anchors for exact matches. attributes: Exact attribute filters as regular expressions, e.g. {"Author": "^jdoe$", "Category": "DAQ"}. date_from: Inclusive range start, 'YYYY-MM-DD' or 'YYYY-MM-DD HH:MM[:SS]'. date_to: Inclusive range end, same formats (time defaults to 23:59:59). last_days: Show entries from the last N days instead of an explicit range. logbook: Logbook name to search, or "*" to search all known logbooks. max_results: Maximum number of entries returned per page (server cap 100000). reverse: Sort newest-first when true, oldest-first when false.

Returns {"total": int, "entries": [{id, logbook?, date_raw, date_iso?, attributes{}, text_excerpt, encoding, encoding_name, attachments[], reply_to[], in_reply_to?, url}]}.

Each entry's text_excerpt is a ~500-char window centred on the first occurrence of the search phrase (when text is provided). The full entry body may contain additional matches; use elog_get_entry for the complete text.

Input Schema

TableJSON Schema

Name	Required	Default
`text`	No
`date_to`	No
`logbook`	No	*
`reverse`	No
`date_from`	No
`last_days`	No
`attributes`	No
`max_results`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 25, 2026

TDQS

A5/5.0

Behavior5/5

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

With no annotations provided, the description carries full responsibility and does so thoroughly: it defines regex semantics, inclusive date formats with defaults, server caps for max_results, sort ordering via reverse, and the ~500-character excerpt behavior. It discloses return fields and the important caveat that additional matches may exist in the full body.

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 front-loaded with a one-line summary and then organized into Args and Returns sections. Every sentence adds meaningful operational detail—regex anchoring, date defaults, excerpt size, and the alternative tool—without repetition or filler.

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 complex 8-parameter search tool with no annotations and no schema-level parameter documentation, the description covers all usage aspects: parameter semantics, return structure, behavioral edge cases, and the relationship to elog_get_entry. Nothing an agent needs to invoke it correctly is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate entirely. It explains every one of the 8 parameters, including format, defaults, wildcard behavior, filtering semantics, and pagination implications. This fully supplies the meaning missing from the 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 opens with a specific verb and resource: 'Search logbook entries by full text, attributes, and/or date.' It clearly defines a distinct search capability and even names the sibling elog_get_entry for retrieval of complete entry text, distinguishing search from retrieval.

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 explains when to use this tool versus alternatives: when text matches are only excerpts, it directs the agent to elog_get_entry for the full body. It also clarifies the '*' logbook wildcard and the last_days option for date-based searches. This gives clear usage context and an explicit alternative.

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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