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Set Agent Memory

set_agent_memory

Idempotent

Store or update ONE durable memory entry (key → value) for this user so context survives across sessions — preferences, prior conclusions, working context. Replace semantics per key (reusing a key overwrites it). Do NOT store a number you would later cite as a fact: financial figures come from data tools and carry fact_ids; memory values are never treated as verified figures. Caps: 200 entries / 8000 chars per value. Tier: sp500+ (sample rejected).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`key`	Yes	Memory key (1–128 chars). Reusing an existing key overwrites its value.
`value`	Yes	The note to remember (≤8000 chars). Never store a figure you would cite as a fact — those come from data tools.

Output Schema

TableJSON Schema

Name	Required	Description
`_meta`	Yes	Provenance envelope — data lineage for every MCP response
`memory`	Yes
`created`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 18, 2026

changedOutput schema / properties / _meta / properties / fundamentals_as_of / description

Previous value: -"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to."New value: +"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt in bulk. Use THIS — not `last_updated` — when telling a user how current the cross-sectional fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to. It is a floor for a single filer, not a ceiling: a filer with a live partition receives its filing, facts and ratios intraday (minutes after EDGAR dissemination), so an entity-scoped read may carry a filing newer than this; cross-sectional ranks (factor scores, earnings signals) refresh with the weekly bulk export."

Changed2 schema fields changedJul 25, 2026

addedOutput schema / properties / _meta / properties / fundamentals_as_of

Added value: +{
+  "description": "ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to.",
+  "type": "string"
+}

addedOutput schema / properties / _meta / properties / price_as_of

Added value: +{
+  "description": "ISO timestamp when the price surfaces were last refreshed.",
+  "type": "string"
+}

AddedJul 10, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare idempotentHint=true and destructiveHint=false, and the description complements them with replace-semantics per key, the 200-entry cap, 8000-char value cap, tier restriction, and the fact that memory values are never treated as verified. It also says a sample from a lower tier would be rejected.

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?

Four dense sentences, all carrying necessary information: what the tool does, overwrite semantics, a crucial negative usage rule, and hard limits/tier. No filler and no repetition of schema details.

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?

The combination of annotations, schema, and description fully covers safety, idempotency, limits, tier gating, and the fact-integrity caveat. An output schema exists, so return values need no explanation. An agent has everything needed to decide when and how to call this tool.

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 beyond the schema by emphasizing overwrite-on-reuse semantics and explicitly warning that memory values should never be used as cited facts. This clarifies the intent behind both parameters.

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?

States a specific action ('Store or update ONE durable memory entry') with a clear resource (key → value) and differentiates itself from get_agent_memory and delete_agent_memory. The durable cross-session context purpose is explicit.

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 says when to use it: for preferences, prior conclusions, and working context that must survive sessions. It also gives a clear exclusion: do not store numbers that would later be cited as verified facts, directing those to data tools. The tier restriction adds another concrete usage boundary.

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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