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AgentBus

Test Python License: MIT

The SQLite-Backed MCP Event Bus & Control Surface for Heterogeneous Agent Swarms.

When Cursor, Claude, Antigravity, and Terminal Agents (like Hermes) share a workspace, they usually coordinate through fragile append-only files (log.md). That works until you need SLA timeouts, Human-in-the-Loop (HITL) intercepts, strict schema validation, or cryptographic RBAC.

AgentBus replaces the "Game of Telephone" with a localhost sidecar: a Python MCP server backed by SQLite. No orchestrator runtime lock-in. No heavy cloud dashboard. Just a hyper-fast local pub/sub built for top-tier AI orchestration.

v0.19.0 (August 2026): Release-integrity gates, honest runtime diagnostics, registered Codex/Pi headless adapters, and untrusted-event prompt containment, on top of the MCP Python SDK v2 migration. See the changelog for details.

Note: Install as okf-agentbus (CLI command remains agentbus). Extras: [obs,devex,jupyter,sdk].

⚡ The "Ah-Ha" Moment: Zero-Restart Integration

Already running Aider, OpenHands, or custom agents in tmux panes? Do not kill your sessions. AgentBus features a dual-interface architecture (MCP + CLI). You don't need to wire up JSON configs to test it today. Just prompt your running agent:

"Use your terminal to run agentbus publish --topic okf/handoff --payload '{\"from\":\"grok\",\"to\":\"hermes\",\"summary\":\"Write tests\"}'"

The SQLite bus instantly captures it, without requiring the MCP server. Once you're convinced by the Mission Control TUI, you can wire up the strongly-typed MCP server for your next boot.

Related MCP server: Hivemind

Why AgentBus?

Alternative

Limitation

AgentBus

log.md blackboard

No schema, race conditions

Typed topics, monotonic IDs, advisory locks

LangGraph / CrewAI

Same-runtime lock-in

Heterogeneous out-of-process clients (IDE + CLI)

LangSmith

Cloud-only, backward-looking

Local SQLite, forward-looking Execution TUI

Redis pub/sub

Extra daemon, complex setup

Zero-config SQLite, native stdio MCP

Feature Arsenal (v0.3 - v0.18)

  • MCP Python SDK v2 (v0.18): migrated the stdio MCP server while preserving the existing event-store contract.

  • Resilient delivery (v0.16.4): bounded retry with jitter, retry-exhausted dead letters and file spillover for SQLite contention.

  • Async suspend/resume (v0.16): durable waits and correlated wake events let headless agents yield without busy polling.

  • Headless runners (v0.15): opt-in adapters for heterogeneous CLI agents with bounded chain behavior and structured acknowledgements.

  • Wake plane and Go helpers (v0.12-v0.13): platform-packaged workers, role leases, wake ingress and webhook delivery.

  • Jupyter async client (v0.11): from agentbus.jupyter import AsyncAgentBus + %agentbus start — non-blocking polls that yield to the notebook event loop.

  • TypeScript client (v0.11): packages/js/agentbus-client — Node EventEmitter + MCP stdio spawn (@agentbus/agentbus-client, path install for now).

  • God View Mesh (v0.9): Passive OS + MCP observability so silent agents still leave bus footprints (system/mcp, system/fs, system/shell, system/monologue).

  • Mission Control TUI (v0.8+): A rich, keyboard-driven Textual dashboard (agentbus monitor). Trace waterfall, HITL, Wiretap pane, Dark Agent warnings.

  • Pluggable Pydantic Schemas (v0.7): Code-first @bus.topic decorators to enforce strict JSON schemas at the insertion layer.

  • Distributed Context (v0.6): Pass massive context (like git diffs) via --attach. Hard 1MB payload limits prevent context window explosion.

  • Agentic Observability (v0.5): Native OpenTelemetry-style trace_id and parent_span_id lineage.

  • SLA Timeouts & Dead-Letter (v0.4): Prevent phantom deadlocks. If an agent ghosts the swarm, SLA timers route the payload to okf/dead-letter.

  • Swarm RBAC & Droid Proofs (v0.3): Cryptographic JWT/UUID tokens ensure only authorized agents can publish to restricted topics.

  • HITL Intercepts (v0.3): Catch dangerous payloads (e.g., DROP TABLE) and place them in PENDING_APPROVAL for human review via the TUI.

Install

The fastest way (Installs & Auto-wires your IDEs in one step):

curl -sSL https://raw.githubusercontent.com/onicarps/agentbus/main/install.sh | bash

Or manually via pip:

pip install -U "okf-agentbus[devex,sdk]"
agentbus init --apply --producer-id my-agent

Jupyter notebooks:

pip install -U "okf-agentbus[jupyter]"
%load_ext agentbus.jupyter
%agentbus start
# or
from agentbus.jupyter import AsyncAgentBus
bus = AsyncAgentBus()  # AGENTBUS_WORKSPACE or cwd
bus.on_event(print)
await bus.start_background(interval=1.0)

TypeScript (from monorepo checkout):

cd packages/js/agentbus-client && npm install && npm test
# set AGENTBUS_WORKSPACE + agentbus on PATH, then use createStdioMcpClient / AgentBus

Quickstart & Examples

The best way to understand AgentBus is to read our copy-pasteable examples.

See the examples/ directory for 7 flawless, isolated Python scripts covering every feature from basic Pub/Sub to Pydantic Schemas and SLA Timeouts.

# Terminal A — Launch the Mission Control TUI
agentbus monitor

# Terminal B — Publish a handoff
agentbus publish \
  --topic okf/handoff \
  --payload '{"from":"cursor","to":"hermes","summary":"Write tests"}'

Before operating or releasing a workspace, run the read-only diagnostics:

agentbus doctor --workspace /path/to/workspace
agentbus doctor --workspace /path/to/workspace --json

The command inspects the target without publishing to its bus. Write-path and MCP stdio checks run in temporary isolated workspaces. --strict makes warnings (including absent optional Go helpers) fail CI.

God View Observability (v0.9.0):

Track silent agents by wiretapping their operations:

# Intercept MCP tool calls
mcp-serve --wiretap

# Watch file edits and command executions
agentbus watch

# Tail internal agent reasoning logs
agentbus tail

Events will stream into the TUI's Wiretap pane as system/mcp, system/fs, system/shell, and system/monologue topics.

📦 Workspace Isolation (The .agentbus directory)

AgentBus operates on the concept of Workspace Isolation (similar to how git uses .git or Docker uses docker-compose.yml).

The bus and its events are physically scoped to the directory you run it in. This prevents your Swarm from tracking your entire operating system or cross-contaminating different projects.

When you navigate to a specific project folder and run agentbus init or agentbus up, it creates a localized .agentbus/events.db SQLite database specifically for that directory.

1-Click Swarm Orchestration (v0.10.0)

Instead of manually opening 5 tmux panes to start your agents and observability daemons, use the new orchestrator:

cd /path/to/my-project

# 1. Generate a boilerplate .agentbus/swarm.yaml
agentbus up --init

# 2. Boot the swarm (Watchers, Agents, and TUI) in one click
agentbus up

# 3. View running background agents
agentbus ps

# 4. Safely kill the entire swarm
agentbus down

Documentation

For full architectural documentation, see the docs/ directory.

License

MIT — see LICENSE.

Available Tools

10 tools
agentbus_approveC

Approve a pending event so agents can see it on poll.

ParametersJSON Schema
NameRequiredDescriptionDefault
event_idYes
auth_tokenNo
reviewer_idNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.7/5.0
Behavior2/5

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

No annotations exist, so the description must fully disclose behavior. It reveals that the tool changes state (approval) and makes events visible on poll, but omits critical details like required permissions, idempotency, reversibility, or side effects. Mutation tools need richer behavioral context.

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?

Extremely concise (one sentence), which is efficient but arguably too brief given the tool's complexity (3 parameters, no schema coverage, mutation). A few more sentences would improve clarity without losing conciseness.

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?

The tool is a mutation with no annotations and an output schema (not described). The description does not cover what constitutes a 'pending event', the approval workflow, or the response structure. The context is insufficient for an agent to use the tool confidently.

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 0%, yet the description adds no parameter meaning. It does not explain event_id, auth_token, or reviewer_id, leaving the agent to infer from names alone. The description must compensate for missing schema descriptions but fails to do so.

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 explicitly states the verb 'Approve' and the resource 'pending event', and clarifies the effect 'so agents can see it on poll'. This clearly distinguishes it from sibling tools like agentbus_review, suggesting a specific approval step.

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?

No guidance on when to use this tool versus alternatives. It does not provide prerequisites, conditions for use, or exclusions. The sibling tools list is given but not leveraged to explain selection criteria.

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

agentbus_lock_acquireC

Acquire an exclusive advisory lease on a workspace resource.

ParametersJSON Schema
NameRequiredDescriptionDefault
owner_idYes
resourceYes
auth_tokenNo
ttl_secondsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.5/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only states that the lease is 'exclusive' and 'advisory,' but lacks details on what happens if the lock is already held, side effects, or return behavior.

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

Conciseness2/5

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

The description is a single short sentence, which is under-specified for a tool with four parameters and an output schema; it sacrifices necessary detail for brevity.

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

Completeness1/5

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

Given the complexity (4 parameters, output schema, no annotations), the description fails to cover return values, failure modes, or how to use the parameters, leaving significant gaps.

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 0% and the description does not explain any of the four parameters (owner_id, resource, auth_token, ttl_seconds), providing no added 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 'Acquire' and clearly identifies the resource as 'exclusive advisory lease on a workspace resource,' which distinguishes it from siblings like lock_release, lock_renew, and lock_status.

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 provides no guidance on when to use this tool versus alternatives like lock_release or lock_renew, nor any prerequisites or exclusions.

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

agentbus_lock_releaseB

Release a held lease (idempotent if already expired).

ParametersJSON Schema
NameRequiredDescriptionDefault
lease_idYes
owner_idYes
resourceYes
auth_tokenNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3/5.0
Behavior2/5

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

The description mentions idempotency if the lease is already expired, which is a useful behavioral trait. However, with no annotations, the description carries the full burden and fails to disclose authentication requirements, side effects, or what happens if the lease is not held.

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 description is a single, concise sentence with no wasted words. It could arguably add more detail without becoming verbose, but it is efficiently structured.

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?

Given the tool has four parameters and no parameter descriptions in the schema, the description should compensate but does not. The existence of an output schema mitigates the need to explain return values, but overall completeness is lacking.

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?

The input schema has 0% description coverage for parameters, and the tool description does not explain any of the four parameters (lease_id, owner_id, resource, auth_token). This is a critical gap.

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 'Release a held lease', with a specific verb and resource. The sibling tools include acquire and renew, so the purpose is distinct and unambiguous.

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?

Usage is implied by the name and description, but there is no explicit guidance on when to use this tool versus alternatives like agentbus_lock_acquire or agentbus_lock_renew. No exclusions or prerequisites are mentioned.

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

agentbus_lock_renewC

Extend TTL on an active lease (heartbeat).

ParametersJSON Schema
NameRequiredDescriptionDefault
lease_idYes
owner_idYes
resourceYes
auth_tokenNo
ttl_secondsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It only states the basic function (extending TTL) without mentioning side effects, error cases, or required permissions (e.g., auth_token needed).

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 a single sentence with no unnecessary words. It is concise and front-loaded with the key action.

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?

Given the complexity (5 params, 0% schema coverage, and a locking context), the description is insufficient. It fails to explain parameters or output, leaving significant gaps for correct invocation.

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 0%, and the description does not explain any of the 5 parameters. It adds no meaning beyond their names, leaving the agent to infer their purposes.

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 'Extend TTL on an active lease (heartbeat)' clearly specifies the verb (extend) and resource (active lease), and the heartbeat terminology distinguishes it from sibling tools like lock_acquire, lock_release, etc.

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 provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. It only states the action without context.

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

agentbus_lock_statusB

Check lock state without acquiring (no auth required).

ParametersJSON Schema
NameRequiredDescriptionDefault
resourceYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, description discloses an important behavioral trait ('no auth required'), but omits other aspects like idempotency, side effects, or what the lock state entails. Minimal but not misleading.

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?

Extremely concise with no filler. However, the brevity sacrifices clarity on parameter semantics. Front-loaded with key differentiating info.

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?

Despite low complexity and presence of output schema (not shown), the description fails to explain the sole required parameter. Leaves agent guessing about 'resource'.

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 0% and description does not mention the 'resource' parameter at all. No guidance on its meaning, format, or constraints.

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?

Clearly states verb 'Check' and resource 'lock state', distinguishing it from sibling tools like lock_acquire, lock_release, and lock_renew. No 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?

Implicitly indicates when to use ('without acquiring') and notes no auth required, but does not explicitly list alternatives or when not to use. Context from sibling names helps, but description lacks explicit guidance.

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

agentbus_pollA

Fetch events after cursor (at-least-once delivery).

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
topicYes
since_idNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.7/5.0
Behavior4/5

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

The description discloses 'at-least-once delivery', a meaningful behavioral trait indicating possible duplicate deliveries and implied consumption semantics. With no annotations provided, this adds value beyond the schema, though it omits other details like read-only vs. side-effect on the cursor.

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 two short phrases that are front-loaded and contain no redundant information. Every word contributes to the meaning.

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?

Despite having an output schema, the description is too sparse to fully understand the tool's mechanics. It omits parameter semantics, ordering, and error behavior, making it incomplete for correct invocation, especially with no annotations to fill 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 only hints at a 'cursor' without explicitly mapping to the since_id parameter. It does not explain the meaning of limit or topic, so the description fails to compensate for the lack of parameter documentation.

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 fetches events after a cursor, using the verb 'Fetch' and resource 'events'. This distinguishes it from sibling tools like agentbus_publish (writing) and agentbus_status (status checks), and the cursor aspect adds specificity.

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?

Usage is implied by the name and sibling context (polling for events after a cursor), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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

agentbus_publishB

Append one event to the workspace event log.

ParametersJSON Schema
NameRequiredDescriptionDefault
topicYes
payloadYes
trace_idNo
auth_tokenNo
producer_idNo
causation_idNo
parent_span_idNo
schema_versionNo1.0
idempotency_keyNo
sla_timeout_minutesNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It states the core action ('append') but does not mention required authentication, idempotency behavior, potential side effects, or failure modes. The array of metadata fields (auth_token, idempotency_key, etc.) suggests additional behavioral context that is left unexplored.

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 description is a single, clear sentence of ten words, efficiently communicating the primary purpose. It is appropriately front-loaded and lacks extraneous content. While it is very short, it is not overly terse to the point of meaninglessness, earning a high but not perfect score for conciseness.

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?

Given the tool's complexity (10 parameters, 2 required, output schema present), the description is markedly underspecified. It does not explain what constitutes an event, how the workspace context is established, or what the output schema contains. The optional parameters (trace_id, auth_token, idempotency_key) hint at distributed tracing and delivery guarantees, but no such context is provided, making the tool difficult to use correctly without additional assumptions.

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 0%, and the description provides no parameter information whatsoever. The required parameters (topic, payload) are not explained, nor are any of the eight optional parameters. The description's phrase 'workspace event log' only faintly implies that topic and payload constitute an event, but it fails to add any semantic value beyond the raw 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 ('Append') and resource ('workspace event log'), clearly indicating the operation's scope and distinguishing it from sibling tools that handle locks, status, and approvals. It is concise and unambiguous, leaving no doubt about the tool's primary function.

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 implies clear usage context: use this tool to append an event to the workspace log. While it does not explicitly mention alternatives or exclusions, the sibling tools are in different domains (locking, polling, reviewing), so the context is sufficient for an agent to infer when to invoke this tool.

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

agentbus_rejectB

Reject a pending event and notify the originating agent.

ParametersJSON Schema
NameRequiredDescriptionDefault
reasonNorejected by human reviewer
event_idYes
auth_tokenNo
reviewer_idNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It does mention the notification side effect, but it omits critical information such as whether the rejection is permanent, how the event state changes, or any authentication requirements. This is a significant gap for a mutating 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?

The description is a single, concise sentence that immediately communicates the primary action and key side effect. It is front-loaded and contains no filler or redundancy.

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?

Given four parameters, no annotations, and zero schema description coverage, this description is insufficiently complete. It does not explain the lifecycle of the event, the meaning of reviewer_id, or any prerequisites, leaving the agent to rely on the output schema which does not cover these behavioral aspects.

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 0%, and the description provides no parameter details. While event_id and reason may be self-evident from their names, auth_token and reviewer_id are not explained, forcing the agent to guess their purpose and required format.

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 verb 'Reject', the resource 'a pending event', and the side effect 'notify the originating agent.' It is specific and distinguishable from sibling tools like approve and review, which have contrary or different purposes.

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 usage context is implied: use this tool when rejecting a pending event. However, it does not explicitly mention alternatives or when not to use it, nor does it contrast with approve or review, so the guidance is only implicit.

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

agentbus_reviewA

List events pending human approval (hidden from standard poll).

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
topicNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states the basic purpose (listing pending events) but does not clarify whether the operation is read-only, any side effects, authentication requirements, or behavior under different conditions (e.g., empty results). The description is too minimal for a tool without annotations.

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

Conciseness5/5

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

The description is a single, clear sentence that front-loads the core purpose. Every word is necessary; there is no redundancy or extraneous information. It is appropriately sized for the tool's simplicity.

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 existence of an output schema (which covers return values) and the tool's straightforward nature (listing pending events), the description provides the essential context. However, missing details such as filtering behavior or relationship to sibling tools (like agentbus_approve) could be added for completeness, even though the tool is simple.

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%, so the description carries the full burden for parameter meaning. However, the description does not mention the parameters 'limit' or 'topic' at all. While the parameter names are somewhat self-explanatory, the description adds no additional context or usage guidance, which is insufficient given the lack of 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 uses a specific verb 'List' and clearly identifies the resource as 'events pending human approval', making the purpose immediately clear. It also distinguishes the tool from siblings by noting these events are 'hidden from standard poll', implying that other tools like agentbus_status show standard events.

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 implies when to use the tool—to view events that are not visible through the standard poll. It does not explicitly state when not to use it or mention alternatives, but the context of sibling tools (e.g., agentbus_approve for approvals) provides implicit guidance. A higher score would require explicit when/when-not statements.

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

agentbus_statusB

Workspace bus health and topic list.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It only states that the tool returns health and topic list, implying a read-only operation but doesn't mention side effects, authorization needs, or error states.

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 description is very short and front-loaded, but it's a noun phrase rather than a complete sentence. It is efficient but could be improved with a verb.

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 zero parameters and the presence of an output schema, the description adequately explains the tool's purpose and return value. It is sufficiently complete for a simple status-check 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?

No parameters exist, so the baseline is 4. The description adds meaning by specifying what the output covers (health and topic list), which goes beyond the empty 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 the tool returns workspace bus health and topic list, distinguishing it from sibling tools like agentbus_review or agentbus_approve. However, it lacks a verb like 'get' or 'retrieve', making it slightly less directive.

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?

No guidance on when to use this tool versus siblings. The sibling names suggest different purposes (review, approve, lock operations), but no explicit conditions or exclusions are provided.

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. Dates show when Glama detected each change.

  1. 3 tool updatesv0.18.0
    • Addedagentbus_poll
    • Addedagentbus_publish
    • Addedagentbus_reject
  2. 8 tool updatesv0.17.0
    • Addedagentbus_approve
    • Addedagentbus_lock_acquire
    • Addedagentbus_lock_release
    • Addedagentbus_lock_renew
    • Addedagentbus_lock_status
    • Removedagentbus_publish
    • Addedagentbus_review
    • Addedagentbus_status
  3. 3 tool updatesv0.16.3
    • Removedagentbus_poll
    • Addedagentbus_publish
    • Removedagentbus_reject
  4. 8 tool updatesv0.16.3
    • Removedagentbus_approve
    • Removedagentbus_lock_acquire
    • Removedagentbus_lock_release
    • Removedagentbus_lock_renew
    • Removedagentbus_lock_status
    • Removedagentbus_publish
    • Removedagentbus_review
    • Removedagentbus_status
  5. 1 tool updatev0.6.0
    • Changedagentbus_publish2 fields changed
      • addedInput schema / properties / parent_span_id
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "title": "Parent Span Id"
        +}
      • addedInput schema / properties / trace_id
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "title": "Trace Id"
        +}
  6. 4 tool updatesv0.4.0
    • Addedagentbus_approve
    • Changedagentbus_publish1 field changed
      • addedInput schema / properties / sla_timeout_minutes
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "integer"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "default": null,
        +  "title": "Sla Timeout Minutes"
        +}
    • Addedagentbus_reject
    • Addedagentbus_review
  7. 4 tool updatesv0.2.0
    • Addedagentbus_lock_acquire
    • Addedagentbus_lock_release
    • Addedagentbus_lock_renew
    • Addedagentbus_lock_status
  8. 3 tool updatesv0.1.0
    • First observedagentbus_poll
    • First observedagentbus_publish
    • First observedagentbus_status

TDQS

A3.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: publishing vs polling events, reviewing/approving/rejecting pending events, and lock status/acquire/release/renew are all separate actions. No two tools overlap in function.

Naming Consistency4/5

All tools use the 'agentbus_' prefix consistently, but the verb/noun order is not uniform. Event-related tools are verb-only (publish, poll, review), while lock tools use noun-first (lock_acquire, lock_release) and status tools are noun-only (status, lock_status). Despite this, the naming is still predictable and readable.

Tool Count5/5

10 tools is well-scoped for the domain of an agent communication bus. It covers the core event lifecycle (publish/poll), human approval workflow (review/approve/reject), and advisory locking (acquire/release/renew/status) without unnecessary bloat.

Completeness5/5

The tool set covers the full event bus lifecycle: publishing, polling, and health status. The approval workflow is complete with review, approve, and reject. Locking includes status, acquire, release, and renew, leaving no obvious gaps for the stated purpose.

Maintenance

ActivityActive
ResponsivenessNo issues

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