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emem

by Vortx-AI
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Rust
Remote

Compose a memory_token citation handle

emem_memory_token
Read-onlyIdempotent

Create a citation handle for one fact so another agent resolves the exact signed value without re-description. Use for a single verifiable fact across messages or tools.

Instructions

Mint a citation handle, emem:fact:<cell64>:<fact_cid> (or :<state_cid>), that any agent or LLM resolves to the byte-identical signed object. The antidote to referential drift on the value side: hand this one string to another agent instead of re-describing the fact. Validates both components are non-empty and free of the : separator. Memory algebra: the cite operation (https://emem.dev/docs/model.html).

When to use: Call when the agent wants a single rebindable string to cite a place plus an attested fact across messages, threads, agents, or tools, without re-fetching or re-describing it. Pair with emem_verify_receipt on the receiving end to check the signed payload. To cite an OBJECT rather than a single reading, use emem_entity's emem:entity: token. FOR MANY FACTS, USE emem_memory_bundle INSTEAD, and this is a measured cost rather than a style preference. Measured over 131 scalar facts at 12 places across 57 bands: a token is 84 characters and 51 LLM tokens, while the signed value it points at averages 10.9 characters and 5.4 LLM tokens. So N individual tokens cost roughly 9.5x the CONTEXT of simply pasting the N numbers (7.7x by characters; the gap is BPE fragmenting a base32 cid, and LLM tokens are the unit that bills a window), and an N-token prompt hits the context wall SOONER than the plain values would. A bundle is 38 characters and 23 LLM tokens at ANY N up to 256 and resolves in one round trip: it beats individual tokens from N=1 and beats pasting the plain values from N>=5. Individual tokens are for citing ONE fact you must be able to verify later; they are the wrong tool for carrying a set.

Example arguments: {"cell":"defi.zb493.xoso.zcb6a","fact_cid":"cxjiu7l54ujzrpnekp24n4534yojpue4mprddbvevnqtti3lh5bq"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bandNoOptional band key. When set, the minted citation carries the band's tamper-provenance block (class, deterministic, tamper_evidence, trust_rank) so the receiving agent sees the trust class without a resolve round-trip.
cellYescell64, neither component may contain `:`.
fact_cidYes52-char base32-nopad-lowercase content-id of the fact (full 32-byte blake3).
observed_onNoThe fact's source capture date (YYYY-MM-DD) as `/v1/recall` reports it in `sources[].captured_at`. Supplied together with `band` it additionally mints the self-describing `descriptor_token`. A wrong date forges nothing: resolve binds the date to the signed fact and answers 409 on a mismatch.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cellYes
docsNo
grammarNoThe token grammar, so the form can be parsed rather than pattern-matched.
fact_cidYes
cell_tokenNoThe address alone, when you mean the place rather than an observation of it.
memory_tokenYesThe citation to paste: emem:fact:<cell64>:<fact_cid>. Copy it verbatim; a hand-assembled token that is one character wrong still reads as a citation and resolves to nothing.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.3.8
    • addedInput schema / properties / observed_on
      Added value: +{
+  "description": "The fact's source capture date (YYYY-MM-DD) as `/v1/recall` reports it in `sources[].captured_at`. Supplied together with `band` it additionally mints the self-describing `descriptor_token`. A wrong date forges nothing: resolve binds the date to the signed fact and answers 409 on a mismatch.",
+  "type": "string"
+}
  2. Changed1 schema field changedv1.3.4
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "cell": {
+      "type": "string"
+    },
+    "cell_token": {
+      "description": "The address alone, when you mean the place rather than an observation of it.",
+      "type": "string"
+    },
+    "docs": {
+      "type": "string"
+    },
+    "fact_cid": {
+      "type": "string"
+    },
+    "grammar": {
+      "description": "The token grammar, so the form can be parsed rather than pattern-matched.",
+      "type": "string"
+    },
+    "memory_token": {
+      "description": "The citation to paste: emem:fact:<cell64>:<fact_cid>. Copy it verbatim; a hand-assembled token that is one character wrong still reads as a citation and resolves to nothing.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "memory_token",
+    "cell",
+    "fact_cid"
+  ],
+  "type": "object"
+}
  3. Changed1 schema field changedv1.3.1
    • changedInput schema / properties / cell / description
      Previous value: -"cell64 — neither component may contain `:`."New value: +"cell64, neither component may contain `:`."
  4. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral context beyond that, including the token format `emem:fact:<cell64>:<fact_cid>`, validation rules (non-empty, no `:` separator), the resolution guarantees, and the measured cost/context tradeoff. This significantly exceeds the annotation baseline and contains 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 front-loaded with a clear purpose statement and then structured into 'When to use', cost analysis, and example sections. It is longer than many tool descriptions, but every part serves a decision-making or usage purpose. The cost analysis is quite detailed and could be trimmed slightly, but it is directly relevant to choosing between this tool and emem_memory_bundle, so it earns its place.

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 description is exceptionally complete: it explains the purpose, when to use, when not to use, alternatives, cost characteristics, validation behavior, pairing with emem_verify_receipt, and provides an example. Since an output schema exists, the absence of return-value details is acceptable. There are no significant gaps for an agent to misuse 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?

The input schema already provides 100% coverage with descriptions for all four parameters, so the baseline is 3. The description adds value with a concrete example argument set and clarifies how the parameters compose into the token structure. It also mentions the validation constraint on components. It doesn't deeply expand each parameter beyond the schema, but it reinforces and exemplified them well.

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 precise verb and resource: 'Mint a citation handle... that any agent or LLM resolves to the byte-identical signed object.' It clearly distinguishes from siblings by naming emem_entity and emem_memory_bundle as alternatives for different use cases, so the agent knows exactly what this tool does and how it differs.

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 'When to use' section is explicit and detailed: 'Call when the agent wants a single rebindable string to cite a place plus an attested fact...' It also provides alternative tools for objects (emem_entity) and many facts (emem_memory_bundle), plus a strong when-not-to-use warning: 'wrong tool for carrying a set.' This gives clear decision rules.

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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