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Locus

CI PyPI version License: MIT Python 3.11+

Hierarchical markdown-based memory system for autonomous AI agents. Each directory is a room (locus) in the palace, containing specific knowledge navigated on demand. Named for the atomic unit of the Method of Loci.

Core idea: Keep context windows small. Load only the room you need, not the whole palace.


How it works

palace/
  INDEX.md                    ← always read first (~50 lines max)
  global/
    toolchain/
      toolchain.md            ← canonical facts about tools
  projects/
    my-project/
      my-project.md           ← room overview + key files
      technical-gotchas.md    ← specialty: issues & resolutions
      sessions/
        2026-03-02.md         ← append-only session log

An agent reads INDEX.md, navigates to the relevant room, and reads only that room. Session logs accumulate until consolidation merges them into canonical files.

See the wiki for full documentation.


Related MCP server: Strata Memory MCP Server

Quick start

# Install
pip install locus-mcp
# or: uvx locus-mcp --palace ~/.locus  (no install needed)

# Create a palace from the packaged example
locus init ~/.locus
# Edit ~/.locus/INDEX.md to describe your palace

# Run the MCP server
locus-mcp --palace ~/.locus
# or: LOCUS_PALACE=~/.locus locus-mcp

Installation

pip install locus-mcp

Or run without installing using uvx:

uvx locus-mcp --palace ~/.locus

Agent skills

The skill files are the one part of Locus written for a specific runtime. The palace convention, the MCP server, and the recall / lint / index CLIs are runtime-neutral and work from anything that can read a file or speak MCP. The skills in skills/claude/ are written and maintained for Claude Code, and that is the only set shipped here. They are plain markdown with YAML frontmatter, so another runtime is welcome to adapt them. Per-runtime copies used to live in skills/codex/ and skills/gemini/; they were removed because keeping three variants honest cost more than it returned.

Install them from a clone:

git clone https://github.com/Nano-Nimbus/locus.git
cd locus
make install-skills            # copies skills/claude/* to ~/.claude/skills/
make install-skills-dry        # print what would be copied, write nothing

CLAUDE_SKILLS_DIR overrides the destination.

Skill

Command

Description

locus

/locus

Recall, navigate the palace, write rooms and session logs, regenerate indexes

locus-consolidate

/locus-consolidate

Merge session logs into canonical files

locus-audit

/locus-audit

Audit palace health

locus-feedback

/locus-feedback

Record explicit feedback on a palace recall

locus-release

/locus-release

Post-release verification workflow (contributors)

locus-security

/locus-security

Trust tags, nonce discipline, and the locus-security CLI

locus-palace-init

/locus-palace-init

Bootstrap a palace from existing memory files

Agent SDK (Python)

pip install locus-mcp
locus --palace ~/.locus --task "What toolchain conventions are set?"

MCP Server

The locus-mcp command exposes five tools over the Model Context Protocol.

Use stdio for all local integrations (Claude Desktop, Claude Code, Codex, Gemini — default, no extra flags needed). SSE transport is available for network deployments (--transport sse) and requires FASTMCP_HOST=0.0.0.0 to be set explicitly — the server binds to loopback by default.

Tool

Description

memory_list

Returns INDEX.md (no args) or lists a room's files

memory_read

Reads any file in the palace

memory_write

Atomically writes a file (guarded — cannot write to _metrics/, sessions/, .sig/, .security/)

memory_search

Ranked full-text search over the shared FTS5 index (see Recall); ripgrep only without FTS5

memory_batch

Reads up to 20 palace files in a single call — use for multi-room loads

Add --security to enable Ed25519 signature verification on reads and automatic signing on writes. See Security below.

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "locus": {
      "command": "locus-mcp",
      "args": ["--palace", "/path/to/palace"]
    }
  }
}

Or using uvx (no install required):

{
  "mcpServers": {
    "locus": {
      "command": "uvx",
      "args": ["locus-mcp", "--palace", "/path/to/palace"]
    }
  }
}

Cursor / Zed

{
  "mcp": {
    "servers": {
      "locus": {
        "command": "locus-mcp",
        "args": ["--palace", "/path/to/palace"]
      }
    }
  }
}

Environment variable

All clients support LOCUS_PALACE as an alternative to --palace:

export LOCUS_PALACE=~/.locus
locus-mcp

See MCP Server Configuration for the full client setup guide and spec/mcp-server.md for architecture details.


Recall

locus recall answers "what do I already know about this?" in one call, fast enough to run on every prompt from a hook. It keeps a SQLite FTS5 index (standard library only, no PyYAML) over any number of markdown roots: a palace, an OKF bundle, a Claude Code memory directory, or all of them at once.

locus recall --root ~/memory --root ./docs "why does the flux kustomization stall"
Recalled memory:
1. Flux healthcheck stall (human-reviewed, 2026-08-22)
   /home/me/memory/project_flux-healthcheck-stall.md
   Flux Kustomization with wait:true stalls on health checks for a bad revision ...
2. [STALE] Old Flux bootstrap procedure (unverified, 2025-11-02)
   /home/me/docs/runbooks/flux-bootstrap.md
   Bootstrap Flux with a personal access token ...

Flag

Default

Meaning

--root DIR

.locus.toml, then LOCUS_PALACE

Directory to index; repeatable

-k N

3

Number of hits

--budget BYTES

4096

Hard cap on text output

--include journal

off

Include type: Journal files

--type TYPE

all

Only this frontmatter type; repeatable

--json

off

Print a JSON list instead of text

--refresh

off

Rebuild the index from scratch

Frontmatter drives the result: title (or name, or the first heading), description, tags, type (or metadata.type), modified (else generated.at, else file mtime), status, stale_after, and verified. Ranking is bm25 with title and description weighted above the body; exact ties go to human-reviewed files, then to the newest modified. A hit is flagged STALE when its stale_after has passed or its status is deprecated. Trust tiers follow OKF: unverified, machine-confirmed (only non-human verified entries), human-reviewed (any verified entry whose by starts with human:).

Roots can live in a .locus.toml in the project or any parent directory:

[recall]
roots = ["docs", "~/memory/shared"]

The index is stored at ${XDG_CACHE_HOME:-~/.cache}/locus/<hash-of-roots>.sqlite, never inside a root, and is refreshed incrementally (mtime, then content hash) on every call. With no hits the text output is empty and the exit status is still 0, so a prompt hook can call it unconditionally:

#!/bin/sh
# Claude Code UserPromptSubmit hook: whatever this prints is injected as context.
prompt=$(jq -r .prompt)
exec locus recall -k 3 --budget 4096 "$prompt"

The MCP server's memory_search uses the same index, so MCP results are ranked the same way. Full rules in spec/recall.md.


Lint and index

locus lint checks markdown roots for Open Knowledge Format v0.2 conformance and the Locus palace conventions. locus index generates the index files those conventions define. Both read the same frontmatter recall indexes, and neither imports the Agent SDK, so a CI job that only checks conformance does not install it.

locus lint  --root docs --check          # CI gate: exit 1 on any error
locus lint  --root docs --fix            # add inferable fields, rewrite nothing
locus index --root docs --check          # exit 1 when a generated index drifted
docs/runbooks/valve-chatter.md: error [okf.type-missing] frontmatter has no non-empty type (fix: add type: Runbook)
docs/log.md: error [okf.log-order] entries run oldest first: 2026-05-09 follows 2026-05-01
docs/reference/platform.md: warning [locus.size-limit] 214 lines exceeds the 200-line soft limit for a specialty file
2 error(s), 1 warning(s), 1 fixable

lint

Flag

Default

Meaning

--root DIR

.locus.toml, then LOCUS_PALACE

Directory to check; repeatable

--check

off

Exit non-zero on any error. For CI

--strict

off

Treat warnings as errors under --check

--fix

off

Add inferable fields. Never rewrites an existing key

--type-map DIR=TYPE

none

Infer this OKF type under DIR; repeatable

--archive-glob GLOB

none

Paths that should carry status: deprecated; repeatable

--json

off

Print a JSON report instead of text

Rules split in two. okf.* checks what the specification requires: a parseable frontmatter block with a non-empty type on every non-reserved document, an index.md with no frontmatter beyond a bundle-root okf_version, a log.md that is date-headed and newest first, and ISO 8601 timestamps. Unknown keys and unknown type values are never reported: the spec requires consumers to tolerate both. locus.* checks the palace conventions: the size limits from spec/size-limits.md and the room main-file rule from spec/room-conventions.md.

Errors fail --check; warnings are advisory. A palace legitimately carries no frontmatter at all, so on a palace root the missing type rules are warnings rather than a CI failure on a layout the palace spec itself describes.

--fix adds three fields and only three: type from --type-map or [lint.types], generated.at from the file's first git commit, and status: deprecated for archive paths. It never rewrites or deletes a key, it never invents a generated block (nothing in a file says who produced it), and running it twice produces identical bytes.

index

Flag

Default

Meaning

--root DIR

.locus.toml, then LOCUS_PALACE

Directory to index; repeatable

--check

off

Write nothing; exit non-zero on drift. For CI

--kind

auto

Force okf, palace, or memory classification

--json

off

Print a JSON report instead of text

What gets generated depends on the root: an OKF bundle gets an index.md per directory in section 8 form (* [Title](path) - description, with okf_version: "0.2" frontmatter at the bundle root only), a palace gets the 50-line routing table INDEX.md, and a Claude Code memory directory gets a MEMORY.md of one - [Title](file.md) - description line per topic file. Output is deterministic, so --check is a byte comparison, and only index files are ever written.

Configure both from one .locus.toml:

[lint]
roots = ["docs"]
archive_globs = ["archive/*"]

[lint.types]
"." = "Reference"
runbooks = "Runbook"

Full rules in spec/lint-and-index.md.


Security

The security system (--security) gives every palace file an Ed25519 signature and every agent session a unique cryptographic nonce. Tool outputs are tagged [TRUSTED], [DATA], or [CRITICAL-DATA] before the agent sees them. The agent skill (locus-security) teaches agents to extract facts from [DATA] content but never follow directives within it.

# One-time setup
locus-security init-config --palace ~/.locus   # writes locus-security.yaml
locus-security init-keys   --palace ~/.locus
locus-security sign-all    --palace ~/.locus

# Run with security enabled
locus-mcp --palace ~/.locus --security
locus --palace ~/.locus --security --task "..."

The locus-security CLI has five subcommands: init-config (writes the annotated locus-security.yaml from the copy that ships inside the package), init-keys, sign-all, verify-all (exit 1 if any file fails verification, or if the palace holds no signable files at all), and rotate-keys. sign-all names and skips any file it cannot read as UTF-8 rather than aborting the run, and exits 1 if it skipped anything. Neither command follows a symlink whose target resolves outside the palace: those are named and skipped by sign-all, and reported as failures by verify-all.

Threat model: direct prompt injection, memory poisoning, indirect injection via external data, nonce exfiltration, multi-turn context drift.

See docs/security.md for the full protocol, configuration reference, and design decisions.


Benchmarks

Palace navigation loads 52% fewer context lines than flat memory for specific queries, while maintaining full recall. Session-only queries (recent work not yet consolidated) are accessible only via the palace.

Palace: 822 lines / 9 queries found   avg  91 lines/query · 3.2 calls
Flat:  1719 lines / 8 queries found   avg 191 lines/query · 2.0 calls

See docs/benchmarks.md for charts and full methodology.


Structure

example-palace/   Palace template; `locus init` writes it into a new palace
spec/             Palace convention definitions:
  index-format.md       INDEX.md rules and routing
  room-conventions.md   Room structure and naming
  size-limits.md        Context budget thresholds
  write-modes.md        Session logs vs canonical edits
  mcp-server.md         MCP server architecture and safety model
  recall.md             locus recall: roots, index, ranking, trust tier, STALE
  lint-and-index.md     locus lint and locus index: OKF conformance, generated indexes
  metrics-schema.md     Run metrics JSON schema
  audit-algorithm.md    Palace health scoring
  health-report-format.md  Audit report structure
  inferred-feedback.md  Disagreement signal classification
templates/        Templates for INDEX.md, rooms, session logs, locus-security.yaml
                  (`locus init --show list`; both trees ship inside the wheel)
skills/
  claude/         SKILL.md files for Claude Code + Agent SDK (the only maintained set)
    locus/              Recall, palace navigation, writes, index and lint
    locus-consolidate/  Room consolidation
    locus-audit/        Palace health audit
    locus-feedback/     Recall quality feedback
    locus-palace-init/  Bootstrap a palace from existing memory files
    locus-release/      Post-release verification (contributors)
    locus-security/     Security conventions (trust tags, nonce discipline)
docs/
  architecture.md       Mermaid diagrams — palace, MCP, security, agent interfaces
  benchmarks.md         Benchmark results and charts (palace vs flat, security overhead)
  onboarding.md         Step-by-step agent onboarding guide
  security.md           Full security protocol, key management, config reference
  bench/                Per-version benchmark JSON (read by generate-charts.py)
scripts/
  bench-mcp.py          45-case MCP integration benchmark (includes security + batch)
  bench-compare.py      Palace vs flat recall comparison
  generate-charts.py    Regenerate docs/img/ charts (reads docs/bench/ automatically)
locus/
  agent/          Python Agent SDK (CLI + metrics)
  audit/          Palace health auditor (locus-audit CLI)
  feedback/       Inferred feedback classifier
  mcp/            MCP server (locus-mcp CLI) — palace.py, server.py, main.py
  conform/        locus lint and locus index: OKF conformance, index generation
  recall/         locus recall: FTS5 index shared with memory_search
  security/       Ed25519 security system — keys, signing, taint, nonce, middleware
  scaffold.py     locus init: packaged templates and palace scaffolding
  utils.py        Shared utilities (slug_from_path)

Roadmap

Milestone

Status

Focus

v0.1 - Foundation

✅ Complete

Spec, conventions, size limits

v0.2 - Core Palace

✅ Complete

Templates, skills, Agent SDK, benchmark

v0.3 - Performance Metrics

✅ Complete

Context tracking, feedback, suggestions

v0.4 - Self Evaluation

✅ Complete

Palace audit, health reports, inferred feedback

v0.5 - MCP Server

✅ Complete

MCP server with memory_list/read/write/search

v0.6 - Public release

✅ Complete

Benchmarks, docs, CI, PyPI

v0.7 - Remote MCP Server

✅ Complete

SSE transport, Bearer auth, Docker image, K8s deploy

v0.8 - Auto-Memory Bridge

✅ Complete

Claude Code auto-memory detection, memory_batch tool

v0.9 - Security System

✅ Complete

Ed25519 signing, taint tracking, nonce watermark, --security flag


Contributing

See CONTRIBUTING.md for dev setup, test instructions, and PR guidelines.

License

MIT

Available Tools

5 tools
memory_batchA

Read multiple palace files in a single call.

paths is a list of paths relative to the palace root (maximum _MAX_BATCH_PATHS entries). Returns all files joined by \n---\n, each section headed by ## <path>.

Missing files, directories, and path-traversal violations are noted inline and do not raise exceptions, so partial results are always returned for valid calls. Raises ValueError only for invalid arguments (e.g. more than _MAX_BATCH_PATHS paths).

Returns an empty string for an empty paths list.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathsYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavior: returns joined files with headers, handles missing/invalid paths inline without exceptions, raises ValueError for invalid args, returns empty string for empty list. Transparent about internal constant _MAX_BATCH_PATHS.

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?

Concise two-paragraph description, no redundancy. Front-loaded with purpose, then clear parameter descriptions. Every sentence adds value.

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 simple parameter (one array) and existence of output schema, the description covers input expectations, return format, error handling, and edge cases (empty list, missing files). Complete for this tool.

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?

Schema coverage is 0%, but description adds meaning: 'paths' is a list of relative paths with a maximum count, and explains format. Provides enough context beyond the bare schema.

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 it reads multiple palace files in a single call, specifying the action (read multiple) and resource (palace files). It differentiates from siblings like memory_read (single file) and memory_write (write operation).

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

Usage Guidelines4/5

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

Provides context on when to use (batch reading) and behavior details (max paths, partial results). Does not explicitly list alternatives but implies usage for multiple files versus single file reads.

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

memory_listA

List the palace index or the files within a room.

Call without path (or with an empty string) to retrieve INDEX.md, the top-level routing table for the palace. Pass a relative room path (e.g. "global/networking") to list the markdown files in that room.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden of disclosing behavioral traits. It states the tool lists files (implied read-only) and differentiates between index retrieval and room listing. It does not mention side effects, permissions, or error handling, but the behavior is predictable and non-destructive. The presence of an output schema compensates for missing return value details.

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 two sentences long, each carrying distinct, necessary information. It is front-loaded with the core purpose, then provides specific usage details. No word is wasted, and the structure makes it easy to scan.

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 the tool has one optional parameter, no required fields, and an output schema, the description covers the primary use cases. However, it does not specify what happens if an invalid path is given (e.g., non-existent room), and it mentions 'markdown files' specifically, which might imply only .md files are listed. These are minor gaps, but the description is mostly complete for a simple list tool.

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

Parameters5/5

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

The input schema has no descriptions (0% coverage), so the description must add all parameter meaning. It fully explains the 'path' parameter's role: empty string retrieves the index, a room path lists files. This completely compensates for the schema's lack of documentation, making the parameter semantics crystal clear.

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 lists the palace index or files within a room, with specific behavior for empty vs non-empty path. It distinguishes the two main use cases and uses a specific verb ('list') and resource structure ('palace index', 'room files'). This is precise and leaves no ambiguity about the tool's purpose.

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

Usage Guidelines4/5

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

The description provides clear guidance on when to call without path (to retrieve INDEX.md) and when to pass a room path (to list files in that room). It does not explicitly mention when not to use this tool or suggest alternatives like memory_search or memory_read, but the usage context is well-defined and easy to follow.

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

memory_readA

Read a file from the palace.

path is relative to the palace root (e.g. "global/networking/networking.md"). Returns the full file contents as a string, prefixed with [TRUSTED] or [DATA] when the security system is active.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the return is a string prefixed with [TRUSTED] or [DATA] under security conditions. However, it omits details about error handling (e.g., missing file) or if the tool is read-only, leaving gaps.

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 extremely concise with three sentences: one for core purpose and two for path format and return value. Every sentence adds essential information with no wasted words.

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 the tool's simplicity (one parameter, no annotations, but has an output schema), the description covers the key aspects: what it reads, how to specify the path, and the return format with security prefix. It lacks error behavior but is fairly complete for a read tool.

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?

The schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'path is relative to the palace root' and provides a concrete example, giving context beyond the raw schema.

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 clearly states 'Read a file from the palace,' providing a specific verb and resource. While it distinguishes from sibling tools like memory_write and memory_search, it does not explicitly differentiate from memory_batch, which could also read files. Still, the purpose is well-understood.

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?

The description gives a path format example but offers no guidance on when to use this tool versus alternatives like memory_list or memory_search. There is no mention of prerequisites, context, or when not to use it.

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

memory_writeA

Write content to a file within the palace.

path is relative to the palace root. The write is atomic (write to a temp file, then rename). Writes to _metrics/, sessions/, or archived/ are rejected, as are non-text file extensions.

Creates parent directories as needed.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYes
contentYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description fully bears the burden of disclosing behavior. It reveals the write is atomic (temp file then rename), rejects writes to certain directories and non-text extensions, and creates parent directories as needed. This goes beyond a simple 'write' statement, though it omits whether overwriting occurs or error handling.

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 concise (3 sentences) with front-loaded purpose and no redundant information. Every sentence adds value: purpose, path semantics, atomicity, restrictions, and directory creation.

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 that an output schema exists (context confirms), the description does not need to explain return values. It covers key aspects: path behavior, atomicity, restrictions, and directory creation. However, it could mention overwrite behavior or error cases for completeness.

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 0%, so the description must compensate. It adds meaning for 'path' (relative to palace root, restricted directories, non-text extensions) but for 'content' only mentions 'content' without format details. The description partially fills the gap but not fully.

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 'Write content to a file within the palace.' with specific verb and resource. It differentiates from siblings like memory_batch (batch writes) and memory_read (read). The additional details about path, atomicity, and restrictions reinforce the purpose.

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?

While the description provides important usage constraints (path relative to palace root, atomic write, rejected paths/extensions, creates parent dirs), it lacks explicit guidance on when to use this tool versus alternatives like memory_batch for batch operations. The context is implicit rather than directly stated.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 5 tool updatesv0.10.0
    • First observedmemory_batch
    • First observedmemory_list
    • First observedmemory_read
    • First observedmemory_search
    • First observedmemory_write

TDQS

A4.1/5.0

Scored across 5 tools

Disambiguation5/5

Each tool targets a distinct operation: batch read, list directory, single read, full-text search, and write. There is no overlap in functionality.

Naming Consistency5/5

All tools follow a consistent 'memory_verb' pattern (batch, list, read, search, write), making it easy to infer purpose from name.

Tool Count5/5

Five tools cover the core operations for a file-based memory system without being excessive or insufficient.

Completeness3/5

CRUD operations are covered except for delete/remove; a delete tool is missing, which could hinder agents needing to clean up files.

Maintenance

ActivityMaintained
ResponsivenessUnresponsive

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    B
    maintenance
    Persistent memory for AI agents enabling saving, searching, and managing knowledge across sessions with local markdown files.
    2
    -