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cuba_zafra

Maintain active project memory: decay, prune, merge, summarize, rank, deduplicate, export, re-embed observations, and apply power-law decay to episodes to keep the graph accurate.

Instructions

Memory maintenance, scoped to the active project: decay, prune, merge, summarize, pagerank, find_duplicates, export, reembed, decay_episodes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cNoPower-law c parameter for decay_episodes (default 0.1)
betaNoPower-law β exponent for decay_episodes (default 0.5)
actionYesdecay: stratified exponential decay by type. prune: deletes low-importance observations, dry-run unless confirm=true. merge: deduplicates similar entities. summarize: replaces an entity's observations with compressed_summary. stats: counts. pagerank: personalized importance ranking. find_duplicates: lists near-duplicate pairs. export: writes a JSON dump. reembed: re-encodes with the current model. decay_episodes: power-law decay on brain_episodes.
confirmNoprune only: actually delete. Without it, prune returns a dry-run plan (would_prune, by_project) and deletes nothing — read the plan first, the default threshold reaches a large share of a mature corpus.
thresholdNoImportance threshold for prune (default 0.1)
batch_sizeNoMax observations to re-encode in reembed (default 500)
entity_nameNoEntity to summarize (for summarize action)
allow_secretNoRefused when the text looks like a live credential (token, password, URL with embedded creds). Set true only for a false match — the text is then stored verbatim, in clear, and reachable by search, export and every client.
halflife_daysNoGlobal halflife override for decay (overrides per-type stratification)
compressed_summaryNoCompressed text replacing observations (for summarize)
similarity_thresholdNoSimilarity threshold for merge (default 0.8)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.25.0
    • changedInput schema / properties / action / description
      Previous value: -"Consolidation action. decay_episodes applies power-law decay to brain_episodes."New value: +"decay: stratified exponential decay by type. prune: deletes low-importance observations, dry-run unless confirm=true. merge: deduplicates similar entities. summarize: replaces an entity's observations with compressed_summary. stats: counts. pagerank: personalized importance ranking. find_duplicates: lists near-duplicate pairs. export: writes a JSON dump. reembed: re-encodes with the current model. decay_episodes: power-law decay on brain_episodes."
    • addedInput schema / properties / allow_secret
      Added value: +{
      +  "description": "Refused when the text looks like a live credential (token, password, URL with embedded creds). Set true only for a false match — the text is then stored verbatim, in clear, and reachable by search, export and every client.",
      +  "type": "boolean"
      +}
    • addedInput schema / properties / confirm
      Added value: +{
      +  "description": "prune only: actually delete. Without it, prune returns a dry-run plan (would_prune, by_project) and deletes nothing — read the plan first, the default threshold reaches a large share of a mature corpus.",
      +  "type": "boolean"
      +}
  2. First observedv0.18.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden, yet 'maintenance' hides that several actions (prune, decay, merge, reembed) mutate or delete data. It says nothing about reversibility, confirmation requirements, or the dry-run default for prune, all of which matter for an unannotated multi-action tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence establishes purpose and scope before the action list, with no filler. The action enumeration partially duplicates the schema enum, costing a point.

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

Completeness2/5

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

For a ten-action dispatcher with destructive operations, no annotations, and no output schema, the description is too thin: it omits safety posture, confirmation behavior, and any differentiation from the parallel memory_zafra sibling. An agent would need to open the schema to understand the tool at all.

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% and each parameter is thoroughly documented in the schema (including confirm's dry-run semantics and allow_secret's credential refusal), so the description adds nothing beyond listing action names already present in the enum. Baseline 3 applies.

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?

The description names a resource (memory) and a scope (the active project) and enumerates the nine operations the tool performs, so an agent can tell it is a maintenance dispatcher rather than a read/write CRUD tool. It falls short of a 5 because the opaque name 'cuba_zafra' is never explained and it does not distinguish itself from the near-identical sibling memory_zafra.

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?

'Scoped to the active project' is the only contextual hint; there is no statement of when to reach for this tool versus its siblings (cuba_zafra vs memory_zafra) or which of the ten actions fits a given situation. Action-level guidance lives only in the schema, not the description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.