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max-ramas

RMS Memory MCP

rms_search

Search project memory using semantic queries across vault (Markdown) or code corpora. Returns a decision envelope with ranked results or abstains when relevance is insufficient.

Instructions

Search RMS Memory. Returns a decision envelope: {decision: inject|abstain, reason, injected_ids, results}. corpus=vault (default) searches human Markdown memory; code searches derived semantic code; all ranks each corpus independently and combines them with Reciprocal Rank Fusion, never raw vector distances. Pass projects: [key, …] for read-only cross-project federation (when both project and projects are set, projects wins so injected rules stay compatible); vault/all across multiple projects requires every listed key to have cross_project_vault=true (hard error otherwise — no silent degrade). Weak matches abstain when min_score is set; content is bounded by max_chars.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of chunks to return. Default is 10.
queryYesThe semantic query string to search for.
corpusNoCorpus to search. Defaults to vault.
projectNoRegistered project key, used when the MCP client did not provide a workspace root. Ignored when `projects` is also set.
projectsNoExplicit list of registered project keys for read-only federated search (max 8 after dedupe). Does not change the active bind. When set together with `project`, this list wins. Vault/all with len>1 requires cross_project_vault=true on every listed key.
max_charsNoMaximum total characters of injected content across results (default 2000). Truncates/drops weaker hits to stay within budget.
min_scoreNoOptional minimum relevance in 0..1 (distance and RRF normalized). If the best hit is weaker, rms_search abstains with an empty results list (fail-closed).
min_confidenceNoOptional minimum confidence threshold (0.0–1.0). Records with NULL confidence are always included. CAUTION: do NOT use high values (e.g. 0.9+) unless you need strict filtering. If zero results, retry without this parameter.
include_contentNoWhether to include full chunk text in results.
Behavior4/5

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

Without annotations, the description carries the full burden. It discloses RRF behavior, abstention logic, content bounding, and cross-project federation rules. Missing explicit read-only declaration but implied by 'search' and 'read-only federation'. Rate limits or auth not mentioned but not critical for a search tool.

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?

Three dense sentences with no wasted words. Front-loaded with purpose and return envelope. Every sentence adds crucial behavior detail (RRF, federation, abstention, budget). Perfectly sized for a tool with 9 params and complex logic.

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 no output schema, the description adequately explains the return envelope. Parameter count 9, all covered. Edge cases (err on missing cross_project_vault, abstention, project preference) are documented. An agent can correctly invoke the tool without additional knowledge.

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?

Schema coverage is 100%, so baseline is 3. The description adds substantial meaning: explains RRF rationale, project vs projects precedence, error condition for cross_project_vault, abstention when min_score set, and content truncation with max_chars. This goes far beyond the schema descriptions.

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 searches RMS Memory and returns a decision envelope. It distinguishes from siblings by specifying three corpora (vault, code, all) and explaining RRF for 'all', which differs from rms_code_search (which likely only searches code) and read tools.

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 usage context: e.g., setting min_score to force abstention, caution about min_confidence, and prerequisites for cross-project federation. However, it lacks explicit when-not-to-use guidance or comparison to alternative search tools like rms_read or rms_code_search.

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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