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brain-v42

Memoria persistente para agentes de codificación, servida a través de MCP.

brain-v42 ofrece a Claude Code, Codex y cualquier otro cliente MCP un segundo cerebro duradero: decisiones, aprendizajes, fragmentos de código, runbooks, ADRs, tickets y hojas de ruta de proyectos — almacenados en PostgreSQL, recuperados mediante búsqueda de texto completo + semántica con reranking, y consolidados cada noche por un pipeline de agentes.

  • Conocimiento tipado, no un volcado de notas — una decisión registra su POR QUÉ y sus alternativas; un fragmento registra su intención; un runbook registra pasos ejecutables. Cada tipo tiene su propio ciclo de vida (cadenas de sustitución, aceptación de ADR, validación de aprendizajes).

  • Ciclo de vida de sesión explícito — el usuario controla cada límite de sesión. Las sesiones capturan los artefactos que produjeron, y el cierre es a prueba de fallos: una sesión termina con conocimiento capturado o con una razón explícita de «nada que capturar», nunca en silencio.

  • Búsqueda con ranking — búsqueda semántica con pgvector + FTS de PostgreSQL, fusionados y reordenados por un cross-encoder.

  • Consolidación nocturna («dream») — un pipeline de agentes limpia enlaces huérfanos, fusiona duplicados, sintetiza aprendizajes y propone promociones, tras killswitches por fase que se distribuyen todos cerrados.

  • Multiproyecto — enfoque por proyecto con revisiones compare-and-swap, hojas de ruta, tickets entre proyectos.

Arquitectura

Claude Code / Codex (MCP client)
       │ HTTP loopback :8765/mcp (production) · stdio (dev/fallback)
  brain-v42 (FastMCP)
       ├── SQLAlchemy async ─▶ PostgreSQL 16 + pgvector   (source of truth)
       ├── HTTP ─────────────▶ embedding endpoint :8003   (optional, pluggable)
       ├── HTTP ─────────────▶ :8003/rerank               (optional reranker)
       └── bolt ─────────────▶ Neo4j 5 Community          (relationship index, optional)

Transporte MCP: producción = bucle local HTTP http://127.0.0.1:8765/mcp; configuración predeterminada y dev/fallback = stdio.

PostgreSQL es la única fuente de verdad. Neo4j es una proyección desechable alimentada por un ledger relacional/outbox — siempre se puede reconstruir desde PostgreSQL, nunca al revés. La ruta canónica está activa en producción desde el 22 de julio de 2026; el diseño y la evidencia viven en docs/ARCHITECTURE.md y en el runbook del graph ledger.

Los embeddings son opcionales y conectables. El propio servidor es agnóstico al modelo: solo habla un contrato HTTP de tres rutas (POST /embed, POST /embed/query, POST /rerank) y degrada con elegancia cuando el endpoint no está disponible — brain_search cae en la búsqueda de texto completo, las escrituras persisten con un embedding NULL y se rellenan después. Cualquier servidor que implemente ese contrato funciona. La pila de referencia incluida (services/) sirve Qodo-Embed-1-1.5B como GGUF mediante llama.cpp en una GPU local. EMBEDDING_DIMENSION se elige en la instalación; cambiar de modelo más adelante implica volver a generar los embeddings del corpus (scripts/regen_embeddings.py).

Related MCP server: Muninn

Inicio rápido

git clone https://github.com/hawkixs/brain-v42 && cd brain-v42
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

# 1. Local Neo4j secret (skip if you run without the graph)
install -d -m 0700 .secrets
read -rsp "Neo4j password (same value as NEO4J_PASSWORD in .env): " PW
(umask 0022; printf 'neo4j/%s\n' "$PW" > .secrets/neo4j-auth); unset PW

# 2. Databases (PostgreSQL 16 + pgvector, Neo4j)
docker compose up -d

# 3. Migrations
export POSTGRES_URL="postgresql+asyncpg://brain:REPLACE_WITH_PASSWORD@localhost:5433/brain"
BRAIN_ALEMBIC_ALLOW_PROD=1 alembic upgrade head

# 4. Run the MCP server (stdio)
python -m brain_v42.mcp.server

Conéctalo a Claude Code — el .mcp.json en la raíz del repositorio ya apunta al endpoint de bucle local HTTP de producción; para una configuración de desarrollo simple con stdio:

claude mcp add brain-v42 -- python -m brain_v42.mcp.server

BRAIN_ALEMBIC_ALLOW_PROD solo se requiere cuando el nombre de la base de datos es exactamente brain; mantenlo como una opción de un solo comando, nunca exportado de forma persistente. Alembic rechaza los parámetros de consulta del DSN; usa la forma simple anterior con host, puerto, usuario y contraseña presentes.

Herramientas MCP

Dominio

Herramientas

Búsqueda y listado

brain_search, brain_list, brain_get, brain_update, brain_delete

Recorrido del grafo

brain_get_neighbors, brain_graph_path

Ciclo de vida de sesión

brain_session_start, brain_session_list, brain_session_resume, brain_session_capture, brain_session_heartbeat, brain_session_end, brain_session_abandon

Contexto de proyecto

brain_set_project_context, brain_update_project_focus, brain_list_projects, brain_list_project_groups

Decisiones

brain_log_decision, brain_supersede_decision, brain_get_supersession_chain

Aprendizajes

brain_learn, brain_validate_learning

Fragmentos

brain_save_snippet, brain_use_snippet

Runbooks

brain_create_runbook, brain_get_runbook, brain_execute_runbook

ADRs

brain_propose_adr, brain_accept_adr, brain_deprecate_adr, brain_list_adrs

Coordinación

brain_ticket_create, brain_ticket_reply, brain_ticket_transition, brain_ticket_list, brain_ticket_get

Dream / grafo

brain_get_clusters, brain_backfill_links_batch, brain_consolidation_candidates, brain_merge_entities, brain_refresh_entity, brain_reindex_plans, brain_list_orphans_for_classification, brain_assign_domain, brain_list_curation_proposals

Roadmap y decadencia

brain_get_roadmap, brain_feature_create, brain_feature_update, brain_decay_status

Guía de flujo de trabajo

brain_workflow_guide

Catálogo completo con firmas: docs/MCP_TOOLS.md.

El perfil de catálogo predeterminado es compact: las siete herramientas del ciclo de vida de sesión permanecen visibles, y cualquier otra herramienta se alcanza a través de dos puertas de enlace — brain_find_tool para descubrir, brain_call_tool para invocar. Establece BRAIN_MCP_PROFILE=native para exponer todas las herramientas directamente.

Sesiones

El usuario controla cada límite de sesión: start, resume, end y abandon son comandos explícitos, nunca inferidos por un hook, un agente o un cliente. Las sesiones capturan los artefactos duraderos que produjeron en un ledger exclusivo, y el cierre es a prueba de fallos: conocimiento capturado o una razón explícita de «nada que capturar», nunca silencio.

Después de 24 horas sin un heartbeat, una sesión abierta expone is_stale=true; el marcador se deriva, el estado persistente sigue siendo open, y solo la limpieza del servidor a los 7 días abandona una sesión sin un comando explícito del usuario.

El contrato completo del ciclo de vida (reglas de captura, semántica de enfoque, informe) vive en docs/MCP_TOOLS.md; el contrato es v4 y sigue evolucionando.

Configuración (.env)

# Required
POSTGRES_URL=postgresql+asyncpg://brain:REPLACE_WITH_PASSWORD@localhost:5433/brain

# Optional — semantic search and reranking
EMBEDDING_SERVICE_URL=http://localhost:8003
EMBEDDING_DIMENSION=1536
RERANKER_URL=http://localhost:8003

# Optional — relationship graph (safe defaults for a fresh environment)
GRAPH_ENABLED=false
GRAPH_LEDGER_WRITE_ENABLED=false

# Tool catalog profile
BRAIN_MCP_PROFILE=compact   # compact (default) or native

LOG_LEVEL=INFO

Nunca coloques MCP_HTTP_TOKEN ni MCP_HTTP_DREAM_TOKENS en el .env compartido: los tokens de portador viven en un archivo privado 0600 (~/.config/brain-v42/mcp-token.env), y la credencial del proyector de grafos en el suyo propio (~/.config/brain-v42/graph-projector.env). Referencia completa — cada variable, los archivos secretos privados, los preflights y los portones de despliegue: docs/OPERATIONS.md.

Modelo de confianza de red

El despliegue apunta a agentes personales en una LAN de confianza. MCP, PostgreSQL y Neo4j se vinculan a loopback; las métricas y la automatización usan loopback por defecto.

Topología de embeddings: producción/valor predeterminado = endpoint unificado local http://localhost:8003; deploy/dev-pc es una ruta de rollback/referencia superada.

El reranker comparte el endpoint unificado de embeddings :8003/rerank. Trata :8003 como expuesto a la LAN hasta que hayas comprobado el enlace real por ti mismo, y nunca lo expongas — ni el puerto MCP — a Internet. El código del repositorio por sí solo no demuestra un estado de firewall real.

Modo Dream

Pipeline de agente nocturno (scripts/dream.sh: scan → clean → connect → synth → promote → reorg) más trabajos del lado del servidor de extracción de tickets, curación de hojas de ruta y limpieza de sesiones. Cada fase mutante está tras un killswitch y todos los killswitches se distribuyen cerrados; el dry-run es el valor predeterminado distribuido. Cada fase se ejecuta con una lista de permitidos de herramientas MCP exacta. Detalles: docs/ARCHITECTURE.md y docs/OPERATIONS.md.

Estado de producción

El objetivo de migración del repositorio es la migración 045. Ninguna página de este repositorio demuestra una cabecera de esquema en vivo — mídela, no la leas aquí:

docker exec brain_v42_postgres psql -U brain -d brain -Atc "select version_num from alembic_version;"

El build en ejecución se nombra a sí mismo: GET /health devuelve version (la distribución instalada) y alembic_head (la revisión incluida), ambos medidos, nunca escritos a mano.

Desarrollo

pytest tests/unit -v                          # no PostgreSQL required
pytest --cov=brain_v42 --cov-report=term-missing
ruff check src/ tests/ && ruff format --check src/ tests/
mypy src/
  • Stack: Python 3.12+, FastMCP 3.x, SQLAlchemy 2.0 async + asyncpg, Alembic, Pydantic 2, structlog.

  • TDD es obligatorio — rojo, verde, refactor; los tests nunca se editan para que el código pase.

  • Umbral de cobertura: 60% (CI bloquea por debajo).

  • La cadena de herramientas de desarrollo está fijada exactamente (pip install -e ".[dev]") para que el entorno local siempre coincida con CI.

Estructura del proyecto

brain-v42/
├── src/brain_v42/
│   ├── config.py              # pydantic-settings — single config surface
│   ├── db/                    # SQLAlchemy engine + tables
│   ├── models/                # Pydantic models
│   ├── repositories/          # CRUD + FTS + pgvector + graph adapters
│   ├── services/              # business logic, embedding, reranker, dream, dedup
│   ├── metrics/               # sidecar + collector + cockpit endpoint
│   ├── automation/            # independent webhook/dedup runtime (:9201)
│   └── mcp/                   # FastMCP server + brain_*/dream_* tool handlers
├── tests/{unit,integration}
├── alembic/versions/          # migrations (shipped inside the wheel)
├── scripts/                   # operational CLIs (dream.sh, canaries, repair)
├── services/                  # GPU embedding service + shim + supervisor
├── deploy/                    # systemd units, per-host compose, install.sh
└── docs/                      # ARCHITECTURE, SCHEMA, MCP_TOOLS, OPERATIONS, runbooks

El grafo de módulos de nivel superior se mantiene acíclico en CI (scripts/check_module_layering.py): cualquier módulo puede extraerse a un servicio independiente sin arrastrar un ciclo consigo.

CI/CD

Etapas: lint → test → security → build. Barreras de seguridad: pip-audit, bandit, gitleaks, comprobaciones de pines de imágenes de contenedor. Las imágenes Docker se construyen y se publican en main; no hay etapa de despliegue — el rollout a un host es siempre un paso manual y fuera de banda. Los lanzamientos están impulsados por etiquetas: el raíl de release construye la wheel + sdist, demuestra que la wheel incluye sus migraciones, y adjunta ambos al release de GitHub.

Versionado

  • La versión distribuida es 0.2.0, y se mantiene en 0.x a propósito: un 1.0.0 prometería una interfaz estable y un camino de retorno, y este proyecto no tiene ni lo uno ni lo otro todavía.

  • No se promete una degradación sin pérdida, en ninguna versión. Dos migraciones rechazan su propio downgrade: 037 lanza una EXCEPTION de SQL en cuanto se perdería una captura de sesión, y 039 lanza una excepción a menos que el operador pase un opt-in explícito -x.

  • Revertir un esquema es, por tanto, un procedimiento del operador con un runbook, nunca una garantía de versión — restaura desde una instantánea en su lugar.

Licencia

Código fuente: Apache-2.0.

Los pesos del modelo no están cubiertos por esa licencia, y esto no es una formalidad. El modelo de embedding de producción, Qodo/Qodo-Embed-1-1.5B, se publica bajo QodoAI-Open-RAIL-M — una licencia con restricciones basadas en el uso, no una permisiva. Ningún peso se almacena ni se distribuye mediante este repositorio: cada modelo se descarga de su host de origen en el momento de la compilación, por el operador, quien acepta los términos de cada modelo directamente de su editor. Consulta NOTICE antes de redistribuir cualquier cosa.

Available Tools

11 tools
brain_call_toolA

Call a tool by name with the given arguments.

Use this to execute tools discovered via search_tools.

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYesThe name of the tool to call
argumentsNoArguments to pass to the tool

TDQS

A3.7/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'Call a tool by name' and does not mention potential side effects, error behavior, dynamic execution risk, or that it can invoke arbitrary tools with arbitrary consequences. This is a significant gap for an execution 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?

Two sentences, zero filler, action stated first. The second sentence provides essential context (use after search_tools) without redundancy. Excellent front-loading.

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

Completeness3/5

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

For a simple 2-parameter tool, the description covers the core action and usage context. However, without an output schema or annotations, it omits return value behavior and error handling, which an agent might need when invoking arbitrary tools. It is adequate but not comprehensive.

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 coverage is 100%, so the schema already documents both parameters. The description adds marginal value by linking parameters to 'given arguments' from search_tools, but does not enrich semantics beyond the schema. Baseline 3 is appropriate.

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 a specific verb ('Call') and resource ('a tool by name with the given arguments'), and differentiates itself from discovery tools by positioning it as the execution step after search_tools. This makes it unambiguous against siblings like brain_find_tool.

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 phrase 'Use this to execute tools discovered via search_tools' gives clear context of when to invoke it (after discovery) and implies it is not for searching. It does not explicitly exclude session-management siblings, but the usage context is sufficient for a generic dispatcher.

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

brain_find_toolA

Search for tools using natural language.

Returns matching tool definitions ranked by relevance, in the same format as list_tools.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language query to search for tools

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It discloses that the tool returns definitions rather than executing tools, indicates relevance ranking, and references the list_tools output format. It does not explicitly state lack of side effects, but the search/return framing makes the read-only behavior clear enough.

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 short sentences with no filler. The action is front-loaded and the return behavior is described in the second sentence. Every word earns its place.

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?

For a one-parameter, output-schema-bearing search tool, the description is complete: it states the query source, the result type, ranking behavior, and output format. No critical invocation information is missing.

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 the single 'query' parameter is already described as a natural language query. The description adds no additional semantic detail beyond the schema, so the baseline of 3 is appropriate.

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 a specific action ('Search for tools') and resource ('tool definitions'), and adds that results are ranked by relevance. This differentiates it from session lifecycle tools and brain_call_tool without ambiguity.

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 its use case: natural-language discovery of tools, as opposed to session manipulation or direct tool invocation. However, it does not explicitly name alternatives or state when not to use it, such as preferring list_tools for browsing all tools.

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

brain_session_abandonB
DestructiveIdempotent

Abandon a session only from an explicit user command.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
reasonYes
session_idYes
expected_client_keyYesClient identity expected for the addressed session UUID. The pair must match before any session mutation. This is an isolation guard, not authentication.

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, which cover the destructive nature. The description adds the explicit-user-command constraint and notes that only an agent tracer session is server-managed. However, it does not describe consequences (e.g., irreversibility, impact on session data) beyond the annotation.

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?

Two concise sentences, front-loaded with the primary action and constraint. The second sentence adds relevant context about the agent tracer without bloat.

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 mutation tool with three required parameters and no output schema, the description is sparse. It does not explain what 'abandon' entails versus brain_session_end, what the response contains, or prerequisites beyond the schema. The annotation and schema cover only part of the operational context.

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

Parameters1/5

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

Schema description coverage is only 33% (only expected_client_key has a description). The tool description provides no parameter information, failing to compensate for the low coverage. An agent receives no guidance on session_id or reason beyond the schema's minimal type constraints.

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 states a clear action ('abandon a session') and resource, and adds a critical constraint ('only from an explicit user command'). It does not explicitly differentiate from the sibling brain_session_end, but the user-command qualifier hints at a distinct lifecycle role.

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 gives explicit when-to-use guidance ('only from an explicit user command') and when-not-to-use ('no hook and no auto-close may invoke this lifecycle boundary'). It does not name alternative tools directly, but the constraint is unambiguous.

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

brain_session_bindA
Idempotent

Bind an open operator session to one focus slot, from an explicit user command.

Once per session; binding the same slot again is a replay. From then on the session's end writes that slot only, never the project base: expected_focus_revision is the slot revision returned here. Refusals: session_not_open, session_is_agent_trace, session_already_bound, slot_not_found, slot_closed, slot_project_mismatch, slot_busy.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
slot_idYes
session_idYes
expected_client_keyYesClient identity expected for the addressed session UUID. The pair must match before any session mutation. This is an isolation guard, not authentication.

Output Schema

ParametersJSON Schema
NameRequiredDescription
slot_idYes
slot_bodyYes
session_idYes
slot_revisionYes

TDQS

A3.9/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly=false, idempotent=true, destructive=false), and the description goes further: it explains the downstream effect that `end` writes only the bound slot and never the project base, enumerates all seven refusal codes, and states the replay rule. This is unusually rich disclosure and consistent with the idempotentHint.

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?

The key action and trigger are front-loaded in the first sentence, then constraints and refusals follow. The prose is dense with internal jargon and the refusal list is unglossed, but every sentence carries substantive information rather than filler.

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?

With an output schema present, return values need not be described, and the description adequately covers lifecycle rules, replay behavior, and failure modes. Its one real gap is the near-total absence of input-parameter meaning, which is left to a thin schema.

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

Parameters2/5

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

Schema coverage is only 33%, with just `expected_client_key` documented inline. The description explains none of the three input parameters (slot_id, session_id, expected_client_key); the only parameter it references, `expected_focus_revision`, is not an input at all. It therefore fails to compensate for the coverage gap.

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 opening clause states a specific verb and resource: 'Bind an open operator session to one focus slot.' It clearly belongs to the session lifecycle family, though it never names a sibling (e.g. brain_session_end/start) to disambiguate which lifecycle call to pick, so it stops short of full sibling differentiation.

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?

It gives a clear triggering condition ('from an explicit user command') and a negative constraint ('no hook and no auto-close may invoke this lifecycle boundary'), plus once-per-session/replay semantics. What is missing is an explicit comparison to the adjacent lifecycle siblings an agent might otherwise choose.

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

brain_session_captureA
Idempotent

Attach durable artifacts from an explicit user command — to repair or refine.

No longer a compulsory ritual. With derived capture armed, artifacts created during the session are attributed without this call, and end no longer demands a receipt. What this tool is for now: attaching something the derivation could not see — created outside the window, on another connection, or in another project — and saying so on the record.

It never steals: an artifact already attributed stays where it is.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
session_idYes
knowledge_idsYes
expected_client_keyYesClient identity expected for the addressed session UUID. The pair must match before any session mutation. This is an isolation guard, not authentication.

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already cover idempotency and non-destructiveness; the description adds that already-attributed artifacts are left in place and that this is not a compulsory step. It does not disclose return behavior, permissions, or failure modes, so with annotations lowering the bar, this is adequate but not rich.

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

Conciseness3/5

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

Purpose and usage are front-loaded in the first paragraphs, but the explanation includes redundant historical context ('No longer a compulsory ritual' followed by the derived-capture explanation) and a final lifecycle sentence that is tangential. It is readable but not every sentence earns its place.

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

Completeness3/5

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

For a side-effecting 3-parameter tool with no output schema and with annotations, the description provides enough usage context to call correctly, including scope and idempotent ownership behavior. It lacks explicit statements about return values or errors and uses jargon like 'derived capture' and 'receipt' without definition, so completeness is only moderate.

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?

The schema describes only expected_client_key; the description adds meaning for knowledge_ids as durable artifacts and specifies their suitability (outside window/connection/project), plus the 'never steals' rule for already-attributed IDs. It does not discuss session_id or expected_client_key beyond schema, so it only partially compensates for the 33% schema description coverage.

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 first sentence identifies a specific action ('Attach durable artifacts') and trigger ('from an explicit user command'). Later text narrows the scope to artifacts the derivation could not see, which differentiates it from automatic capture, though it does not name sibling 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 explicitly states when to use the tool: for artifacts created outside the session window, on another connection, or in another project. It also says when it is not needed, because derived capture attributes normal session artifacts and `end` no longer requires a receipt. It stops short of naming sibling alternatives, but the when/when-not guidance is strong.

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

brain_session_endA
DestructiveIdempotent

End a session from an explicit user command, on judgement alone.

nothing_to_capture_reason is now OPTIONAL. The old rule — a non-empty ledger XOR a written reason — measured whether the client had DECLARED its work. Derived capture feeds that signal from the server, and a check is hollow the moment the thing it checks can influence its own signal; worse, it made a session whose ledger the server had filled impossible to close. Give a reason if you have one to give; a blank one is still refused, because saying nothing and saying " " are not the same act.

What end still requires is what the server cannot produce for you: a summary and a next focus. It REPORTS unattributed_in_window — artifacts of this project created during the session that belong to no ledger — as a measure, never a gate. It cannot refuse a close, and a session cannot improve it by doing nothing.

For a bound session, expected_focus_revision is the SLOT revision (from bind, resume, or relay's slot.revision), never started_focus_revision.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
summaryYes
next_focusYesJugement et engagements pour la session suivante — ce qui n'est pas dérivable automatiquement (ex : ne pas publier ce brouillon et pourquoi, une échéance et sa raison, une décision opérateur à respecter). N'y recopie pas l'état mesurable (révision de schéma, HEAD git, arbre propre, résultat de suite de tests) : il est déjà recalculé à chaque briefing depuis la source réelle, et une copie manuelle se périme en silence.
session_idYes
expected_client_keyYesClient identity expected for the addressed session UUID. The pair must match before any session mutation. This is an isolation guard, not authentication.
expected_focus_revisionYes
nothing_to_capture_reasonNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
sessionYesPersistent state of one explicitly controlled concurrent session.
replayedYes
focus_diffNo
focus_at_endYes
current_focusYes
focus_outcomeYesPersisted outcome of the one focus update attempted while ending.
focus_revision_at_endNo
current_focus_revisionYes
unattributed_in_windowYes
remaining_open_session_countYes

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare destructiveHint/idempotentHint/readOnlyHint=false, so the safety profile is covered. The description goes beyond them with substantive behavior: nothing_to_capture_reason is now optional, a blank-string reason is still rejected, `unattributed_in_window` is reported as a measure and cannot gate the close, and summary/next_focus are server-underivable requirements. It stops short of 5 because it never says what happens to the session record after the close or whether the operation is reversible.

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

Conciseness3/5

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

The purpose is front-loaded in the first sentence, which is good. But several sentences are rhetorical justification for a design decision ('a check is hollow the moment the thing it checks can influence its own signal', 'saying nothing and saying " " are not the same act') that consumes space without changing how an agent calls the tool.

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?

An output schema exists, so return values need not be explained, and the description covers the lifecycle constraint, the required-judgement inputs, and the revision-slot trap. It is nearly sufficient for a 6-parameter destructive lifecycle tool; the missing piece is an explicit statement of how to choose this over brain_session_abandon.

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 description coverage is only 33%, so the description must compensate, and it does for the two least-obvious parameters: expected_focus_revision is pinned to the SLOT revision from bind/resume/relay and explicitly not started_focus_revision, and nothing_to_capture_reason's new optionality plus blank-refusal rule is spelled out. summary, session_id, and nothing_to_capture_reason's value shape remain undocumented in both places, keeping it below 5.

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 opening sentence gives a specific verb+resource ('End a session') and adds the operative scope ('from an explicit user command, on judgement alone'), which an agent can act on. It does not, however, name or contrast against the obvious sibling brain_session_abandon, so the boundary between the two lifecycle endings is left to inference.

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?

It states both a positive trigger (explicit user command, agent judgement) and an explicit prohibition ('no hook and no auto-close may invoke this lifecycle boundary'), which is real when/when-not guidance. The gap is that it never names the alternative tool (brain_session_abandon) for the case where a session should be terminated without a summary/focus.

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

brain_session_heartbeatA

Refresh an open session from an explicit user command.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
session_idYes
expected_client_keyYesClient identity expected for the addressed session UUID. The pair must match before any session mutation. This is an isolation guard, not authentication.

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, so the mutation is known. The description adds that this is a lifecycle boundary and only for explicit commands, but it does not explain what 'refresh' does to the session (e.g., extends timeout) or any side effects. It adds some context but not deep behavioral detail.

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, zero wasted words. The main purpose is front-loaded, and the critical usage constraint is stated immediately after. Perfectly concise.

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

Completeness3/5

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

For a mutation with no output schema, the description is somewhat bare. It does not specify behavior for a closed session, failure modes, or the return value. The agent can infer that the session must be open from the phrase 'open session', but it is not explicitly guaranteed. Given the simplicity, this is adequate but not complete.

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 coverage is 50%: session_id has only a format, while expected_client_key has a detailed description. The tool description itself does not elaborate on either parameter. Since the missing session_id is self-explanatory (a UUID), the description does not need to compensate much, but it still adds no meaning beyond the 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 uses a specific verb ('refresh') with a clear resource ('an open session') and immediately distinguishes itself from siblings by stating it is the only lifecycle boundary invoked by explicit user command, not by hooks or auto-close. This fully differentiates it from brain_session_start/end/resume.

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 explicitly states when to use the tool ('from an explicit user command') and, more importantly, when not to use it ('no hook and no auto-close may invoke this lifecycle boundary'). This gives the agent a clear decision rule, even though alternatives are not named directly.

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

brain_session_listA
Read-onlyIdempotent

List sessions only in response to an explicit user command.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
statusNoopen
project_keyNo

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safe read-only nature is established. The description adds meaningful behavioral context beyond those annotations: the server only auto-opens/closes an agent tracer session, and hooks/auto-close must never invoke this boundary. This is valuable context, though it does not describe list ordering, pagination, or return shape.

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 short sentences with no filler. The primary action is front-loaded, and the critical invocation restriction is placed in the supporting sentence. Every sentence earns its place.

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

Completeness3/5

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

The description fully covers the unusual invocation policy, which is likely the highest-risk aspect of this tool. However, with no output schema and no parameter descriptions, the agent still lacks context about what a session entry contains, which status filters mean, and what the list response looks like. Adequate for basic invocation but with meaningful gaps.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not compensate for any of the four parameters. The schema provides names, types, defaults, and the status enum, but meanings like 'stale', 'abandoned', and 'closed_inactive' are left unexplained, and project_key semantics are not addressed. With zero coverage, the description should add parameter context but does not.

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 states a clear verb and resource ('List sessions') and adds a distinctive policy constraint: it runs only on explicit user command. It does not explain what kinds of sessions are returned or how this differs from sibling read tools, but the core purpose is unambiguous.

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 gives an explicit when-to-use condition ('only in response to an explicit user command') and an explicit when-not-to-use condition ('no hook and no auto-close may invoke this lifecycle boundary'). It does not mention sibling alternatives, but the trigger and exclusion are clear enough for an agent to decide.

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

brain_session_relayA
DestructiveIdempotent

Relay an open session onto its slot, or its project base: capture, end, restart.

One transaction: the named knowledge_ids are captured into the old session, the handover is written under a compare-and-swap, the old session ends, and a successor opens under new_client_key; its briefing follows. Two forms, and exactly one revision per call.

Bound session: send expected_slot_revision; the handover (at most 4,000 characters) becomes the slot body and the successor stays on the slot. A closed slot or a stale revision changes nothing and leaves the session open.

Unbound session: send expected_focus_revision, the BASE revision; the handover becomes the project's whole base focus and the successor is unbound. A stale revision (focus_revision_conflict) changes nothing and leaves the session open, unlike end, which closes anyway. SHRINK GUARD: a handover under 70% of the current base focus is refused (base_focus_shrink, both lengths in the message), because it REPLACES the whole base: carry the durable content over. Only an operator relay may pass allow_focus_shrink = true; a guard mod never can.

An equal replay returns the same successor with replayed = true; any other payload on an ended session is terminal_conflict. The successor's next end or relay sends result.slot.revision (bound: the SLOT revision, from bind, resume, or relay) or result.focus_revision (unbound: the new BASE revision), never started_focus_revision for a bound one.

A guard mod the operator explicitly enabled may make this call as a standing user command, and only this one (Amendment — slot relay (ADR #34)); with initiator = 'guard_mod' it is refused while BRAIN_SESSION_RELAY_GUARD_MOD_ENABLED is false.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
summaryYes
handoverYes
initiatorYes
session_idYes
knowledge_idsNo
new_client_keyYesStable identity for one intended session. Reuse it for every retry of that session; use a distinct stable key for each parallel session.
allow_focus_shrinkNo
expected_client_keyYesClient identity expected for the addressed session UUID. The pair must match before any session mutation. This is an isolation guard, not authentication.
expected_slot_revisionNo
expected_focus_revisionNo
nothing_to_capture_reasonNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
slotNo
sessionYesPersistent state of one explicitly controlled concurrent session.
briefingNo
replayedYes
focus_revisionNo
ended_session_idYes

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only supply the safety profile (destructive, idempotent); the description adds the substantive behavior: single-transaction CAS semantics, that stale revisions or a closed slot change nothing and leave the session open, the 70% shrink guard and its refusal code, the replayed/terminal_conflict outcomes, and the guard-mod environment gate. This is far beyond what the annotations convey.

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?

Long but front-loaded, with labeled cases (Bound/Unbound/Shrink Guard) that let an agent scan rather than parse prose. Most sentences carry operational payload, though the trailing paragraph about the agent tracer is loosely tied to the call itself.

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?

For a destructive, 11-parameter lifecycle tool with an output schema, it covers transaction shape, guarded failure modes, and revision hand-off to the successor's next call. Remaining gaps: no explanation of `summary` or `nothing_to_capture_reason`, and the handover length figure differs from the schema constraint.

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 description coverage is only 18% across 11 parameters, so the description must compensate, and it does for the critical ones: `expected_slot_revision` vs `expected_focus_revision` (base revision), `handover` content and its replacement semantics, `knowledge_ids` capture, `new_client_key` successor identity, `allow_focus_shrink` operator-only rule, and `initiator`. Gaps remain for `summary` and `nothing_to_capture_reason`, and it states a 4,000-character handover cap that conflicts with the schema's 10,000 maxLength.

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?

States a specific verb and resource ('relay an open session onto its slot, or its project base') and unpacks it into the concrete lifecycle it performs: capture, end, restart via a successor. It explicitly distinguishes itself from the sibling `end` ('unlike `end`, which closes anyway'), so an agent can route between them without opening schemas.

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?

Gives explicit branching conditions: bound sessions require `expected_slot_revision`, unbound sessions require `expected_focus_revision`, and it names the failure modes that select differently. It also states when the tool may be invoked by a guard mod (operator-enabled, env flag on). It doesn't frame the choice against alternatives like `brain_session_capture` or `brain_session_resume` beyond the `end` contrast, so not a full 5.

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

brain_session_resumeB
Read-onlyIdempotent

Resume an open session from an explicit user command.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
session_idYes
expected_client_keyYesClient identity expected for the addressed session UUID. The pair must match before any session mutation. This is an isolation guard, not authentication.

Output Schema

ParametersJSON Schema
NameRequiredDescription
sessionYesPersistent state of one explicitly controlled concurrent session.
briefingNo
slot_closedNo
current_focusYes
open_session_countYes
current_focus_revisionYes

TDQS

B3/5.0
Behavior1/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, yet the description calls this a "lifecycle boundary" that the server "opens or closes," and the schema states the client-key pair must match "before any session mutation." Resuming a session is an intentional state change, so the description directly contradicts the readOnly annotation.

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?

Two short sentences with the primary action stated first and the lifecycle constraint second; no filler. Slightly cryptic phrasing ("agent tracer") costs it a point but the structure is sound.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the description covers the invocation precondition (explicit user command). However, for a mutating lifecycle operation it omits what state changes on resume, error behavior for a closed/unknown session, and any detail on the undocumented session_id parameter.

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

Parameters2/5

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

Schema description coverage is only 50%: expected_client_key is well documented in-schema, but session_id carries no description anywhere. The description adds no meaning about either argument (e.g., which session UUIDs are valid, what happens if the client key mismatches), so it fails to compensate for the coverage gap.

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 specific verb (resume) and resource (an open session) and scopes it to explicit user commands, which separates it from the lifecycle-start path in siblings like brain_session_start. It does not name any sibling explicitly, so differentiation still requires inference from names alone.

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?

"From an explicit user command" gives a clear when-to-use trigger, and the second sentence effectively says when NOT to use it (no hooks, no auto-close). It stops short of naming the alternative to call for a brand-new session, so the routing guidance is good but not complete.

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

brain_session_startA
Idempotent

Start or replay a concurrent session from an explicit user command.

An agent tracer is the only session the server opens or closes on its own; no hook and no auto-close may invoke this lifecycle boundary.

ParametersJSON Schema
NameRequiredDescriptionDefault
client_keyYesStable identity for one intended session. Reuse it for every retry of that session; use a distinct stable key for each parallel session.
project_keyYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
sessionYesPersistent state of one explicitly controlled concurrent session.
briefingNo
replayedYes
open_session_countYes

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover idempotency, destructiveness, and read-only hints. The description adds value by disclosing that this is a controlled lifecycle boundary and that the server only opens/closes agent tracer sessions on its own. This is behavioral context beyond what annotations provide, with no contradiction.

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 with no filler. The main action and trigger are front-loaded, and the second sentence earns its place by preventing incorrect automatic invocation.

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

Completeness3/5

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

The output schema and annotations cover return values and safety traits, so those gaps are acceptable. However, the required project_key parameter is left unexplained, and the relationship between 'start/replay' and the sibling brain_session_resume is not clarified. This is a meaningful gap for an agent deciding which session tool to call.

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

Parameters2/5

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

The description adds no parameter-level meaning. The schema describes client_key well, but project_key has no description and is required; the description does not compensate for that gap. With 50% schema coverage, the description should have provided at least some project/session context.

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 the action ('Start or replay') and the resource ('a concurrent session'), plus the specific trigger ('from an explicit user command'). It does not explicitly distinguish itself from sibling brain_session_resume, and 'replay' vs 'resume' creates some potential overlap.

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 gives explicit when-to-use context: only from an explicit user command. It also gives a clear exclusion: no hook and no auto-close may invoke this lifecycle boundary. It does not name alternatives like brain_session_resume, but the trigger guidance is strong.

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. 3 tool updatesv0.6.7
    • Addedbrain_session_bind
    • Addedbrain_session_relay
    • Changedbrain_session_resume1 field changed
      • addedOutput schema / properties / slot_closed
        Added value: +{
        +  "default": false,
        +  "type": "boolean"
        +}
  2. 9 tool updatesv0.6.1
    • First observedbrain_call_tool
    • First observedbrain_find_tool
    • First observedbrain_session_abandon
    • First observedbrain_session_capture
    • First observedbrain_session_end
    • First observedbrain_session_heartbeat
    • First observedbrain_session_list
    • First observedbrain_session_resume
    • First observedbrain_session_start

TDQS

A3.7/5.0

Scored across 11 tools

Disambiguation4/5

Each of the nine session lifecycle tools targets a distinct action (start, resume, heartbeat, end, abandon, bind, capture, relay, list), and the two meta tools (call_tool, find_tool) are clearly separate. However, the extremely verbose and overlapping conceptual descriptions (repeated 'agent tracer' boilerplate, relay containing capture/end/restart) could still cause occasional misselection between related lifecycle boundaries.

Naming Consistency4/5

All tools use snake_case with a consistent 'brain_' prefix. Session tools follow 'brain_session_<action>' and meta tools follow 'brain_<verb>_tool', which is a minor deviation in pattern but still predictable and readable.

Tool Count5/5

11 tools is well within the ideal range and each tool earns its place: nine cover the complex session lifecycle (create, resume, refresh, end, abandon, bind, capture, relay, list) and two provide dynamic tool discovery/execution. No tools appear redundant or missing from a count perspective.

Completeness4/5

The session lifecycle surface is comprehensive: start, resume, heartbeat, end, abandon, bind, capture artifacts, relay handover, and list. A dedicated 'get_session' or 'status' tool might be a minor gap, but list and resume likely cover most needs, and the meta tools add extensibility.

Maintenance

ActivityActive
ResponsivenessNo issues

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