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Mnemom — Trust Ratings for AI Agents

by io.github.mnemom

put_alignment_by_agent

DestructiveIdempotent

Publish or replace the alignment manifest — Accepts YAML (text/yaml, application/yaml) or JSON. Body is the full UnifiedAlignmentCard; server-side composition merges it across the platform → org → team → agent cascade and writes the canonical composed card. Requires Idempotency-Key. Honor...

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
auditYesHow long this agent's own decision log is kept, and whether it can be queried. Required. (This is the agent's audit policy — it is NOT Mnemom's retention policy for the card itself; see the tool's data-handling disclosure for that.)
valuesYesThe values this agent declares it is bound by. Required.
agent_idYesThe agent this card belongs to (e.g. `smolt-abc123`). Identifier only — never place an API key, a secret, an email address, or any other personal data in this field.
autonomyYesWhat the agent may do on its own authority. Required.
principalYesWhose authority this agent acts under. Required.
card_versionYesCard schema version. REQUIRED by the server-side validator. Current canonical value: `unified/2026-04-26`.
autonomy_modeYesMaster switch for the action-policing pipeline. Required. `off` disables it; `observe` records only; `nudge` warns; `enforce` blocks.
integrity_modeYesMaster switch for the values pipeline. Required. Same four states as `autonomy_mode`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesAlways true on successful storage (errors return non-200 status).
card_idYesCard ID (ac-{uuid}) of the stored alignment card.
issued_atYesISO 8601 timestamp when the card was issued/stored.

TDQS

A4.2/5.0
Behavior5/5

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

The description adds meaningful behavioral context beyond annotations: it discloses server-side composition merging across the platform→org→team→agent cascade, writes the canonical composed card, and requires Idempotency-Key. Annotations already signal destructive and idempotent behavior, and the description reinforces and extends this without contradiction.

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 purpose but becomes a run-on sentence and ends abruptly with "Honor...", which appears truncated. While each segment carries useful information, the structure suffers from the incomplete final clause and the dense single-sentence flow.

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 the tool's complexity (8 params, nested objects) and rich schema plus output schema, the description covers key behavioral aspects: media types, merge cascade, canonical card, and idempotency requirement. It misses explicit return-value discussion (covered by output schema) and the truncated "Honor..." likely indicates more context, but it is still fairly complete.

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 100%, so the schema fully explains all parameters. The description adds only a high-level note that the body is the full UnifiedAlignmentCard, but does not enrich individual parameter semantics beyond what the schema provides. Baseline of 3 is appropriate.

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 verb and resource: "Publish or replace the alignment manifest". It distinguishes from siblings like put_protection_by_agent (protection card) and preview_compose_alignment_by_agent (preview), making its specific purpose unmistakable.

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 context is clear: this is the publish/replace operation for an alignment card, accepting YAML or JSON with a full UnifiedAlignmentCard body. However, it does not explicitly mention alternatives like preview_compose_alignment_by_agent or state when not to use it, so it lacks explicit exclusions.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct operation: identity claiming, lookup, reputation retrieval/badge, scanning, verification, alignment/protection management, and feedback. No significant overlap exists.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern using snake_case (e.g., claim_agent, get_reputation, verify_scan). Even complex names like preview_compose_alignment_by_agent adhere to the pattern.

Tool Count4/5

With 16 tools, the set is slightly heavy but still well-scoped for the domain of AI agent trust ratings. Each tool serves a clear purpose, and no tool feels redundant.

Completeness4/5

The surface covers core workflows: agent identity, reputation, alignment/protection, scanning, verification, and feedback. Minor gaps like agent updates or deletion might exist, but the core lifecycle is complete.

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