Skip to main content
Glama

memory_index

Returns a budgeted index of memory records, one line per record, so an agent can identify and open the right entry without loading the entire store.

Instructions

THE ALWAYS-LOADED INDEX: one line per record, budgeted, so the right one gets opened.

A store too big to hold in context is read through a small index, and the agent decides what to open from those lines alone. The line is therefore the only surface a future need can reach: a record whose line does not distinguish it is present, correct, and never retrieved.

MEASURED on a 316-note store, 120 questions written from the note bodies and shown to no line-writer, ranking all 316 candidates. recall@3 on full questions / on the three-to-eight words someone types into a search box: a hand-written title-and-hook 0.333 / 0.508; the title alone 0.300 / 0.450; title plus its highest-idf terms 0.350 / 0.533; a line saying what the record CONCLUDED 0.683 / 0.833; the full records, as a ceiling, 0.858 / 0.967.

So the line worth having is a sentence about the conclusion, and no extraction produces one -- term-stuffing is a null on both registers. Which is why the useful call is not this one alone: read needs_line, write those sentences yourself, and store them with set_index_line. Without them this returns the fallback -- the record's opening sentence, measured through this same call at 0.442 / 0.525 against 0.692 / 0.842 with written lines -- and limits says which you got.

budget_tokens shortens lines to fit and NEVER drops a record -- a record with no line cannot be found at all -- so a budget too small to hold one line each is reported as exceeded rather than silently met.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
budget_tokensNo
Install Server

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden and it covers key behaviors: fallback to the record's opening sentence, budget_tokens shortening lines, never dropping records, exceeding rather than silently meeting an insufficient budget, and records without lines being effectively unfindable. It leaves the output shape vague (what `limits` contains) and never explicitly states the operation is read-only.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core concept and structured in readable paragraphs, but the benchmark paragraph and repeated quantitative results are not needed to invoke the tool correctly. It is more verbose and discursive than necessary, and phrases like 'term-stuffing is a null on both registers' add conceptual color rather than direct usage guidance.

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?

It covers the main call semantics and failure modes well for a one-parameter tool, and the workflow with set_index_line is a useful addition. However, there is no output schema, the description never defines the exact return shape or the meaning/structure of `limits`, and it references `needs_line` as a step without that tool appearing in the sibling list, leaving an agent uncertain about the full workflow.

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

Parameters3/5

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

Schema description coverage is 0%, and the description does explain that budget_tokens shortens lines to fit and that an inadequate budget is reported as exceeded rather than silently met. However, it does not clarify what the default value 0 means, what units are expected, or what valid ranges look like, so an agent still has meaningful ambiguity about the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies memory_index as the always-loaded index used to decide which records to open from one-line summaries, and states that without written index lines it returns a fallback opening sentence. It is clear about the resource and operation, though it never uses a direct verb like 'returns the index lines' and leans on conceptual framing rather than a plain API statement.

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?

It gives concrete workflow guidance: use needs_line to find records needing lines, write conclusion sentences, store them via set_index_line, and call memory_index to read the budgeted index. It does not explicitly compare against recall/get or list when-not conditions, but the context of using an index for large stores is clear.

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

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DanceNitra/inspeximus'

If you have feedback or need assistance with the MCP directory API, please join our Discord server