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Grep the Octopus API catalog (llms.txt)

grep_llms_txt
Read-onlyIdempotent

Search the Octopus API catalog with grep-style semantics to efficiently find endpoints, sections, or steps without loading the full file.

Instructions

Search the Octopus API catalog at octopus://api/llms.txt with grep-style semantics. The catalog is large (~300+ KB) — call this rather than reading the resource body directly.

llms.txt is structured as:

  • Authentication and Space Selection sections (top of file)

  • Endpoints section: one '### {Category}' heading per resource family (Accounts, ActionTemplates, Channels, Releases, …) and one bullet per endpoint of the form - \METHOD /path` - description | Prefixes (pick one): /{spaceId}, /spaces/{spaceIdentifier} | ?queryParams → ReturnType`

  • Steps section: deployment step types (Octopus.* ActionType) and their configurable property keys.

Useful patterns:

  • 'POST /releases' — find write endpoints under a resource family

  • 'DELETE ' — enumerate delete endpoints

  • '### Channels' — jump to a section heading

  • 'Body: Create.*Command' — find endpoints that take a Create command body

Parameter conventions mirror GNU grep:

  • pattern (regex by default; set fixedString:true for literal text)

  • caseInsensitive (-i)

  • invertMatch (-v)

  • fixedString (-F)

  • beforeContext (-B)

  • afterContext (-A)

  • maxCount (-m)

Response: totalMatches (true count across the whole file), totalLines, the matched lines with 1-indexed lineNumber, optional before/after context arrays, and catalogResourceUri for the structured fall-through.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patternYesRegex (default) or literal substring (when fixedString=true). Tested against each line of llms.txt independently — same model as `grep`.
caseInsensitiveNoEquivalent to grep -i. Default false.
invertMatchNoEquivalent to grep -v: return lines that do NOT match. Default false.
fixedStringNoEquivalent to grep -F: treat pattern as a literal substring, not a regex. Use this when grepping for text containing regex metacharacters. Default false.
beforeContextNoEquivalent to grep -B: lines of preceding context to include with each match. Capped at 50.
afterContextNoEquivalent to grep -A: lines of trailing context to include with each match. Capped at 50.
maxCountNoEquivalent to grep -m: stop returning matches after this many. totalMatches in the response still reflects the true count across the whole file. Hard cap 500.
Behavior4/5

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

Annotations already declare readOnlyHint etc., but the description adds specifics: the catalog is ~300 KB, grep semantics, response structure including totalMatches reflecting true count across the whole file, and the catalogResourceUri. No contradictions.

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 longer but well-structured: purpose, file structure, usage patterns, parameter mapping, response fields. Every sentence adds value, though a minor reduction could improve conciseness.

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 7 parameters, no output schema, the description covers input and output comprehensively. It explains the file structure, parameter details, and response fields. Could include a concrete example, but the provided patterns suffice.

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?

With 100% schema coverage, baseline is 3. The description adds significant value by mapping each parameter to grep flags, explaining pattern behavior (regex vs fixedString), providing hard caps, and detailing maxCount's behavior. This goes well beyond what the schema provides.

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 action ('Search the Octopus API catalog') and the resource ('llms.txt'), with explicit distinction from reading the full resource body. It also positions the tool as a grep-like search, distinguishing it from sibling tools like grep_task_log.

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 advises using this tool instead of reading the resource body directly, provides useful grep patterns (e.g., 'POST /releases', 'DELETE '), and explains parameter conventions. While it doesn't explicitly list when not to use, it implies alternatives.

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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