ephemeral-buffer

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capture_text

Ingest already-collected text into an ephemeral buffer and receive a compact JSON summary with capture metadata. Use it for indexing existing output for hybrid retrieval.

Instructions

Ingest already-collected text and return capture metadata.

Use this when the caller already has output to index. For a noisy or potentially long command, use execute_and_capture so output remains bounded before it reaches the agent context. The return value is a compact versioned JSON summary; optional named metrics are retained in structured_metrics.

Input Schema

TableJSON Schema

Name	Required	Default
`label`	No
`content`	Yes
`content_type`	No	auto
`structured_metrics`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.5.0Sep 19, 2026

addedInput schema / properties / structured_metrics

Added value: +{
+  "anyOf": [
+    {
+      "additionalProperties": true,
+      "type": "object"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Structured Metrics"
+}

First observedv0.2.0Sep 9, 2026

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It explains the return value (compact versioned JSON summary) and that structured_metrics are retained, but it never explicitly states the side effect of ingestion: whether the text is persisted to a capture store, becomes searchable, or has limits/idempotency behavior. Adds context but leaves the core storage behavior implied.

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?

Three short sentences with the main purpose front-loaded, followed by usage guidance and return-value note. Slight redundancy between 'return capture metadata' and 'return value is a compact versioned JSON summary,' but the description earns each sentence and remains efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter tool with no annotations and 0% schema coverage, the description covers the primary use case, a key alternative, and the return shape, and an output schema exists. It is incomplete on side effects and two parameters ('label', 'content_type'), which an agent needs to craft correct calls.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain parameter meaning. It clarifies 'content' by referring to already-collected text and hints at 'structured_metrics' as optional named metrics, but 'label' and 'content_type' (including the 'auto' default) are never explained, leaving significant parameter semantics undocumented.

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 opening sentence states a concrete action ('Ingest already-collected text') and the result (return capture metadata), which distinguishes it from the sibling execute_and_capture. It names what input is expected and what the tool is not for (collecting output from command execution).

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 tells an agent when to use it ('when the caller already has output to index') and when to prefer execute_and_capture for noisy/long commands, with a reason (keeping output bounded before agent context). This routes the agent to the correct sibling without ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.