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mcp_engram_secure_context_provision

Open an encrypted-at-rest ProvLog to provide need-to-know context. Returns a bounded snippet, integrity pointer, and audit trail for selective disclosure.

Instructions

Sovereign selective disclosure: open an encrypted-at-rest ProvLog (XChaCha20-Poly1305) for need-to-know only. Returns bounded snippet + Merkle-related integrity pointer + audit concept. Ritual: process:engram.ritual.secure-context-provision. Env: ENGRAM_ENCRYPT_AT_REST, ENGRAM_SOVEREIGNTY_KEY, ENGRAM_SECURE_CONTEXT. FEW-SHOT: {"concept":"lexicon:word:sovereignty","query":"encrypted","max_chars":512}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional substring to window around (case-insensitive)
conceptYesTarget concept (required)
max_charsNoMax plaintext chars in snippet (default 512, clamp 32–16384)
Behavior4/5

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

With no annotations, the description takes on the burden and does well: it reveals encryption algorithm (XChaCha20-Poly1305), return constraints ('bounded snippet'), and an audit concept. It also surfaces environment dependencies. It does not mention side effects or failure modes, but for a read-like provisioning tool, this is solid disclosure.

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 structured with labeled sections (purpose, returns, ritual, env, few-shot), but it is dense with jargon and acronyms. The main idea is front-loaded, though the Ritual line and environment variable list may be necessary for operation. It is not as concise as it could be but is organized.

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 no output schema and no annotations, the description covers the core needs: what it does, what it returns (snippet, integrity pointer, audit concept), environment prerequisites, and a few-shot example. It lacks failure modes and explicit alternative comparisons, but for a 3-parameter tool, this is reasonably 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% for all three parameters, so the schema does the heavy lifting. The description adds a few-shot example with concrete values ('concept':'lexicon:word:sovereignty','query':'encrypted','max_chars':512) which aids usage, but it does not explain parameters beyond what the schema already provides. Baseline 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 tool's purpose: 'open an encrypted-at-rest ProvLog... for need-to-know only' with a defined output of 'bounded snippet + Merkle-related integrity pointer + audit concept'. The verb 'open' and resource 'ProvLog' are specific, and the encryption/need-to-know framing distinguishes it from sibling tools like mcp_engram_read_concept or mcp_engram_recall.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for secure, need-to-know selective disclosure and lists required environment variables (ENGRAM_ENCRYPT_AT_REST, etc.), which are prerequisites. However, it does not explicitly state when to use this tool versus alternatives or provide exclusions, leaving usage context to inference.

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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