Calera Infinite Context (ICX) — Persistent Memory & Associative Recall

Crystallize Incremental Delta

icx_sync_delta

Extracts fine-grained deltas between previous text/document state and updated state, and crystallizes them into the Volumetric Memory lattice in sub-2ms on CPU with automatic secret scrubbing and SHA-256 deduplication. Use this tool for continuous incremental sync of code files, documentation, PRDs, and database schemas. Mutating operation. Requires X-License-Key authentication.

Input Schema

Name	Required	Description
`uri`	No	Document or file URI identifier (e.g. 'src/backend/engine.go', 'docs/rfc_42.md').
`new_text`	Yes	New updated text/code/document state after modifications. Leave empty for document deletions.
`old_text`	No	Previous text/code/document state before modifications. Leave empty for new document additions.
`space_id`	No	Optional memory space partition. Defaults to 'default'.
`source_id`	No	Optional connector or source identifier tracking provenance for instant purge (e.g. 'github_core', 'cli_watch'). Defaults to 'mcp_sync'.

Output Schema

Name	Required	Description
`uri`	Yes	description=File or document URI
`status`	Yes	description=Crystallization status (VERIFIED_CRYSTALLIZED \| error)
`space_id`	Yes	description=Target memory space partition
`duration_ms`	Yes	description=Sub-millisecond crystallization execution latency
`facts_learned`	Yes	description=New simplicial facts added to lattice
`deltas_processed`	Yes	description=Count of fine-grained deltas extracted
`facts_invalidated`	Yes	description=Obsolete facts unlinked from lattice

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 26, 2026

TDQS

A4.9/5.0

Behavior5/5

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

The description offers deep technical behavioral traits beyond the metadata, including a performance claim ('sub-2ms on CPU'), specific safety protocols ('automatic secret scrubbing and SHA-256 deduplication'), and critical operational requirements ('Requires X-License-Key authentication').

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?

The description is highly optimized, front-loading the core function with technical value propositions (performance, security) and ending with clear scoping and mutation warnings. It avoids filler entirely.

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?

Given the tool's high technical complexity (deduplication, synchronization, memory lattice), the description provides a complete picture of its operational constraints, functionality, and use cases without requiring additional manual lookups.

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?

While the input schema provides 100% coverage, the description adds vital functional context by explaining the nature of the data exchange: `new_text` is the state after modifications and `old_text` is the state before, which is essential for understanding how the delta calculation works.

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 is highly specific, defining the function as extracting 'fine-grained deltas' and 'crystallizing them into the Volumetric Memory lattice.' It immediately distinguishes this delta-sync function from general memory retrieval tasks within the tool suite.

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?

It provides clear and comprehensive use-cases ('code files, documentation, PRDs, and database schemas'). By defining the operation as a 'mutating operation,' it sets the correct expectation for when to invoke the tool.

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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