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engram

engram

by TushaeBXN
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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engram_compress

Compress text or code into Engram Shorthand (ES) to reduce token size while preserving meaning for persistent AI memory across sessions.

Instructions

Compress text into Engram Shorthand (ES).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "engram_compress"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes
is_codeNo
confidenceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.7.0

TDQS

C2.5/5.0
Behavior2/5

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

With no annotations, the description bears the full behavioral burden and discloses almost nothing: it never says whether compression is lossy or reversible, whether ES output is accepted by other tools (decompress, add_memory, etc.), or what confidence/is_code do to the result.

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?

A single front-loaded sentence with no filler, which is structurally clean. But at this length the brevity reflects under-specification rather than disciplined conciseness, so it only earns a middling score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-parameter transformation tool with no annotations, no output schema, and no parameter documentation, the description is far too thin. An agent cannot know what the compressed output looks like or whether the optional parameters matter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate and adds nothing. The 'text' input is inferable from the name, but 'is_code' and 'confidence' (integer 1-5) are completely unexplained — their effect on the compression output is unguessable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (compress) and output artifact (Engram Shorthand). However, 'Engram Shorthand (ES)' is jargon that is never defined, and the description doesn't differentiate this from the sibling engram_decompress beyond the obvious inverse relationship.

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

Usage Guidelines2/5

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

There is no guidance on when to compress versus storing text directly, no mention of the paired engram_decompress tool, and no stated preconditions. The agent must infer all usage context.

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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