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phasespace-labs

palinode

by phasespace-labs
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Hybrid

palinode_search

Read-onlyIdempotent

Search stored memory to retrieve relevant context about people, projects, decisions, insights, or research. Returns semantically ranked excerpts from memory files, helping you quickly find past knowledge.

Instructions

Search Palinode memory for relevant context about people, projects, decisions, insights, or research. Returns the most relevant memory file excerpts ranked by semantic similarity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullNoReturn full chunk content instead of snippets.
tierNoHow much of each hit to return. 'abstract' caps every hit at ~300 chars (summary first) for cheap relevance checks; 'overview' returns frontmatter plus the head of the body; 'full' is the chunk body. Omit to keep the default snippet view.
limitNoMax results to return (default 15)
queryYesNatural language search query
typesNoFilter by memory type (matches frontmatter `type`).
categoryNoFilter by category (memory directory name): people, projects, decisions, insights, research
thresholdNoOverride similarity threshold (0.0-1.0); higher is stricter.
date_afterNoFilter results after an ISO date (e.g. 2024-01-01)
since_daysNoOnly return memories created/updated in the last N days. Equivalent to setting `date_after` to now-N days; the API derives one from the other.
date_beforeNoFilter results before an ISO date
min_priorityNoOnly return memories with human-assigned priority at least this value. Missing priority counts as normal (3).
include_dailyNoInclude daily session notes at full rank (default: false, daily/ files are penalized)
include_telemetryNoInclude machine/monitor telemetry memories.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv0.16.0
    • addedInput schema / properties / tier
      Added value: +{
+  "description": "How much of each hit to return. 'abstract' caps every hit at ~300 chars (summary first) for cheap relevance checks; 'overview' returns frontmatter plus the head of the body; 'full' is the chunk body. Omit to keep the default snippet view.",
+  "enum": [
+    "abstract",
+    "overview",
+    "full"
+  ],
+  "type": "string"
+}
  2. Changed3 schema fields changedv0.13.0
    • changedInput schema / properties / limit / default
      Previous value: -10New value: +15
    • changedInput schema / properties / limit / description
      Previous value: -"Max results to return (default 10)"New value: +"Max results to return (default 15)"
    • addedInput schema / properties / limit / maximum
      Added value: +50
  3. First observedv0.9.5

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already mark this as read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds that results are memory file excerpts ranked by semantic similarity, but does not disclose behaviors like default snippet views or daily-file penalties; those appear only in the parameter schema. No contradiction with annotations.

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?

Two sentences, no filler, with the primary function front-loaded and the output behavior stated second. Every sentence adds value.

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?

The tool has a richly documented schema and safe annotations, and the description covers core purpose and result type. Since there is no output schema, a little more detail about the returned hit structure would help, but for tool selection and invocation the definition is sufficient.

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 all 13 parameters are documented. The description echoes some category labels (people, projects, decisions, insights, research) which map to the category and types filters, but it does not add meaning beyond the schema's parameter descriptions. Baseline 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?

The description names a specific verb ('Search'), a resource ('Palinode memory'), the content scope (people, projects, decisions, insights, research), and the output (relevance-ranked excerpts). This clearly distinguishes it from sibling tools like palinode_read or palinode_push by emphasizing semantic retrieval.

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 the use case: use this when you need semantically relevant context from memory. However, it does not explicitly state when not to use it or name alternatives such as palinode_read or palinode_list, so an agent gets only partial routing guidance.

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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