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SabilMurti

Amneshia

by SabilMurti
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

remember_media

Attach structured knowledge to local media files by ingesting them into content-addressable storage with deduplication, creating entities, recording observations, and linking semantic relations.

Instructions

Ingest an immutable media asset (image, audio, video, PDF, document) into Content-Addressable Storage (CAS) with SHA-256 deduplication. Automatically creates an entity representing the media, records descriptive observations about what the media depicts or contains, evaluates pre-insertion contradiction detection, establishes semantic relations to other entities, and synchronizes to dual-write Markdown.

WHEN TO USE:

  • Use "remember_media" when you have a local media file (screenshot, photo, voice note, document, diagram) and want to attach structured knowledge, descriptions, or relationships to it.

  • Amneshia handles storage, hashing, and relations deterministically with ZERO LLM overhead.

  • To query media facts later, use "recall" or "context".

RETURNS:

  • JSON containing { ok: true, entity, media: { sha256, mimeType, fileName, fileSize, relativePath, deduplicated }, observationIds, relations, contradictionWarnings }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNoAuthority tier for attached observations: invariant, architectural, contextual, ephemeral
factsYesFactual observations describing the media content, context, or visual elements
domainNoDomain namespace (default: "personal")
entityYesEntity name representing this media item (e.g. "Sabil Murti Profile Picture", "Architecture Diagram v3")
filePathYesAbsolute or workspace-relative path to the source media file on disk
relationsNoSemantic relationships linking this media entity to other entities

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses immutability, deterministic hashing/dedup, automatic entity creation, pre-insertion contradiction detection, relation establishment, and dual-write Markdown synchronization. It does not cover permission/auth requirements or failure modes (e.g. missing file, unsupported MIME), which keeps it short of a 5.

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?

Front-loaded with the core action, then cleanly sectioned into WHEN TO USE and RETURNS. Every sentence carries information an agent needs; nothing is padding.

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?

No output schema exists, and the description compensates with an explicit RETURNS block listing the JSON shape (sha256, mimeType, deduplicated, observationIds, relations, contradictionWarnings). Combined with the usage guidance, an agent has everything needed to call it correctly.

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 already documents filePath, entity, facts, tier, domain and relations. The description only loosely links 'records descriptive observations' to facts and adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

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 verb and resource ('Ingest an immutable media asset ... into Content-Addressable Storage') and specifies the mechanism (SHA-256 deduplication). It is clearly distinguishable from siblings like remember, recall, context and forget, which are mentioned by name.

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?

An explicit WHEN TO USE block names the trigger condition (a local media file such as screenshot, photo, voice note, document, diagram) and routes the agent to 'recall' or 'context' for later querying. When-to-use and the alternative-tool path are both spelled out.

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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