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Glama

Random Agent

A powerful MCP server for multi-worker autonomous agent orchestration. Decompose complex tasks, run parallel workers, auto-review, and generate follow-up tasks — all through the Model Context Protocol.

Features

  • Parallel Workers — Run up to 5 concurrent AI agent processes

  • Task Decomposition — Auto-split complex tasks into subtasks with dependencies

  • Auto-Review & Reflection — Coordinator generates reviews and reflections on completed tasks

  • Follow-up Generation — Reflections auto-create new tasks for continuous improvement

  • 22 Assertion Types — Validate outputs with equals, contains, regex, file-exists, json-path, and more

  • Stall Detection — Detect stuck workers, kill them, and auto-retry

  • Real-time Monitoring — Live status dashboard with queue counts and worker states

  • Metrics Collection — Track scores, issues, and patterns over time

Related MCP server: agent-mcp

Installation

git clone https://github.com/randomchips/random_agent.git
cd random_agent
npm install
npm run build

Usage

Add to your OpenCode config (~/.config/opencode/opencode.jsonc):

{
  "mcp": {
    "random-agent": {
      "type": "local",
      "command": ["node", "/path/to/random_agent/dist/index.js"],
      "enabled": true,
      "environment": {
        "AGENT_OS_BASE_PATH": "C:\\agent-os"
      }
    }
  }
}

Tools

Tool

Description

inject

Queue a task with name, command, priority, and optional assertions

orchestrate

Auto-decompose complex task → inject subtasks → monitor → return results

status

Live view: coordinator state, queue counts, active workers

coordinator

Start / stop / restart the background coordinator loop

handle_stuck

Detect stuck workers, kill them, auto-retry failed tasks

assert

Run assertions on task output (22 assertion types)

logs

Read coordinator logs, filter by search term or worker ID

metrics

Read metrics database (scores, issues, patterns)

Pipeline Stages

inject → pending → in-progress → completed → review → reflection → follow-up
  1. Inject — Task queued in task-queue/pending/

  2. Worker — Spawns AI process, executes command

  3. Completed — Task moved to task-queue/completed/

  4. Review — AI generates review saved to reviews/

  5. Reflection — AI generates reflection saved to reflections/

  6. Follow-up — New tasks auto-generated for next cycle

Configuration

Environment variables:

Variable

Default

Description

AGENT_OS_BASE_PATH

C:\agent-os

Base path for all agent data

AGENT_OS_MAX_WORKERS

5

Max concurrent worker processes

AGENT_OS_LOOP_INTERVAL

5

Coordinator loop interval (seconds)

AGENT_OS_STALL_THRESHOLD

90

Seconds before worker is considered stuck

Project Structure

random_agent/
├── src/
│   ├── index.ts              # MCP server entry point
│   ├── types.ts              # TypeScript type definitions
│   ├── services/
│   │   ├── assertions.ts     # Assertion engine (22 types)
│   │   ├── coordinator.ts    # Coordinator lifecycle
│   │   ├── decomposer.ts     # Task decomposition
│   │   ├── file-reader.ts    # File system operations
│   │   └── worker-monitor.ts # Worker health monitoring
│   └── tools/
│       ├── assert.ts         # Assert tool
│       ├── handle-stuck.ts   # Handle stuck workers
│       ├── inject.ts         # Inject tasks
│       ├── lifecycle.ts      # Coordinator control
│       ├── logs.ts           # Read logs
│       ├── metrics.ts        # Read metrics
│       ├── orchestrate.ts    # Full orchestration
│       └── status.ts         # System status
├── package.json
├── tsconfig.json
└── README.md

License

MIT

Contributing

Contributions welcome! Open an issue or submit a PR at github.com/randomchips/random_agent.

Available Tools

8 tools
assertB

Run output comparison assertions on tasks or arbitrary text

ParametersJSON Schema
NameRequiredDescriptionDefault
formatNotext
outputNoRaw text to check (when not using task_name)
task_nameNoCompleted task name to check
assertionsYesAssertions to run

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 behavioral disclosure. However, it fails to mention critical behaviors such as side effects (e.g., 'update-snapshot' may modify state), failure semantics (does it throw an error?), or whether it requires specific permissions. The schema hints at a write capability through 'update-snapshot', but the description omits this entirely.

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 is front-loaded with the core purpose. Every word contributes meaning, and there is no redundant or filler content. It is appropriately terse for the level of detail it conveys.

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 tool with 4 parameters, a wide range of assertion types, no output schema, and no annotations, the description is far too brief. It does not explain how assertions are structured, what happens on success/failure, or how the 'task_name' and 'output' parameters relate. The current description only scratches the surface, leaving the agent to infer most context from the schema.

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 75%, and the schema provides reasonable descriptions for output, task_name, and assertions, while format has an enum. The tool description adds no parameter-specific meaning. At 75% coverage (between 50% and 80%), the schema does most of the work, and the description does not compensate for the remaining gaps.

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 'Run' and the resource 'output comparison assertions' with scope 'on tasks or arbitrary text'. This is specific and distinguishes the tool from its siblings (metrics, status, logs, etc.), none of which suggest assertion functionality.

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 is provided on when to use this tool vs alternatives. The description does not mention any exclusions, prerequisites, or sibling tools that might be more appropriate in certain contexts. The only hint is that it operates on tasks or arbitrary text, but this is implicit rather than actionable guidance.

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

coordinatorB

Start, stop, or restart the coordinator

ParametersJSON Schema
NameRequiredDescriptionDefault
actionYesAction

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It tells what can be done (start/stop/restart) but does not disclose side effects, such as whether restart causes downtime, if operations are asynchronous, or what impact stopping has on other tools. This is minimal disclosure.

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?

One concise sentence contains both the action and resource. It is appropriately sized for a simple lifecycle tool, with no redundant wording or filler.

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?

Given the tool has one parameter and no output schema, the description is minimally sufficient, but it lacks context about what the coordinator is, what happens on each action, or what the result will be. With no annotations or output schema, the agent needs more contextual details to use it reliably.

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 fully defines the single required parameter 'action' with an enum (start/stop/restart) and a description ('Action'). The tool description adds no additional meaning beyond the schema, so a baseline of 3 is appropriate given 100% schema coverage.

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 'Start, stop, or restart the coordinator' clearly identifies the tool's action (start/stop/restart) and its target resource (the coordinator). This distinguishes it from sibling tools like metrics, status, logs, or inject, which are not lifecycle management actions.

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 the coordinator tool versus alternatives (e.g., orchestrate, handle_stuck) or any prerequisites/preconditions. It simply states the action without context, leaving the agent to infer usage.

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

handle_stuckA

Detect stuck/failed workers, kill them, and retry

ParametersJSON Schema
NameRequiredDescriptionDefault
forceNoForce handle all active workers

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral disclosure burden. It does state that the tool kills workers and retries, which signals destructiveness, but omits side effects, reversibility, privilege requirements, and the meaning of the force option.

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, front-loaded sentence of eight words with zero filler. Every word contributes to the core purpose.

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 one-parameter tool with no output schema, the description covers the main action well. However, it lacks usage context, side-effect details, and clarification of the force parameter, so it is not fully 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?

The schema fully describes the 'force' parameter with a clear description, and schema coverage is 100%. The tool description adds no additional parameter semantics, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific action verbs ('Detect', 'kill', 'retry') and names the resource ('stuck/failed workers'), clearly distinguishing handle_stuck from read-only siblings like metrics, status, and logs.

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?

It implies the tool should be used when workers are stuck or failed, but gives no explicit when-to-use or when-not-to-use guidance, nor does it contrast with alternatives like assert or coordinator.

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

injectC

Inject a task into the pending queue

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYesTask name (short, descriptive)
commandYesCommand for the AI agent to execute
priorityNonormal
assertionsNo

TDQS

C2.7/5.0
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 behavioral disclosure. It only implies a mutation ('inject') but fails to mention side effects, required permissions, failure modes, or what happens after injection. This lack of detail fails to inform the agent of potential risks or constraints.

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, front-loaded sentence with no unnecessary words. It effectively communicates the core purpose, though given the tool's complexity (4 parameters), it might benefit from a bit more detail. Still, it is appropriately concise for stating the primary function.

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 tool's complexity (4 parameters, including an assertions array), lack of annotations, and no output schema, this description is severely incomplete. It does not explain return values, verification steps, or how this tool integrates with siblings like assert or handle_stuck, leaving the agent with insufficient information 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 50% (name and command have descriptions, but priority and assertions do not). The description adds no parameter information, forcing the agent to rely solely on the schema. It does not compensate for the missing descriptions of priority and assertions, nor does it clarify the role of the required parameters in the injection process.

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 action ('inject') and the target ('pending queue'), making it distinct from sibling tools like metrics, status, and logs, which are read-only. The verb+resource structure is specific 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 Guidelines2/5

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

No guidance is provided on when to use this tool vs alternatives such as orchestrate or assert. The description only states what it does, leaving the agent to infer usage context without any exclusions or alternative recommendations.

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

logsB

Read real log files from the agent-os system

ParametersJSON Schema
NameRequiredDescriptionDefault
fileNoLog file name (e.g. coordinator.log)
linesNoNumber of recent lines
searchNoSearch term
worker_idNoWorker ID for status file

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 behavioral disclosure. It only states that it reads logs, but does not disclose any side effects, access requirements, output format, or limits. It does not contradict anything, but offers very little beyond the basic action.

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 that states the action and subject without padding. It is front-loaded and easy to parse, though it could arguably be more informative without becoming verbose.

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 that the tool has four parameters, no output schema, and no annotations, the one-sentence description is insufficient. It does not explain what the logs contain, how parameters combine, what the return format is, or how it relates to sibling tools, leaving significant gaps for an agent.

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?

All four parameters have descriptions in the schema (100% coverage), so the schema already documents their meaning. The tool description itself adds nothing about how parameters like 'search' or 'worker_id' interrelate, so it stays at the baseline for high schema 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 description uses a specific verb ('Read') and a clear resource ('real log files from the agent-os system'), making the core purpose obvious. It does not explicitly differentiate from sibling tools like metrics or status, but the term 'real log files' helps distinguish it from aggregated metrics or system status.

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

Usage Guidelines3/5

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

The description implies the tool should be used when you need to inspect actual log file contents, which suggests a basic use case. However, it provides no explicit guidance on when to choose this over sibling tools such as metrics or status, and no exclusions or prerequisites.

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

metricsB

Read real metrics from the metrics database

ParametersJSON Schema
NameRequiredDescriptionDefault
taskNoFilter by task name
limitNoMax recent tasks (default 10)

TDQS

B3.1/5.0
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 behavioral disclosure. 'Read real metrics' implies a non-mutating operation, but it offers no details about output format, filtering behavior beyond the schema, or any caveats about data freshness or access.

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, front-loaded sentence that states the core action and resource without any filler. It is appropriately sized for a simple read tool with two optional parameters.

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 tool is relatively simple with only two optional parameters and no output schema, so a one-sentence description is nearly sufficient. However, in the context of seven sibling tools, the lack of any usage context or clarification of what 'real metrics' means leaves a gap in completeness.

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

Parameters3/5

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

Schema coverage is 100%, with parameters 'task' and 'limit' already documented as filtering and limiting results. The description adds no additional meaning beyond what the input schema provides, so a baseline score of 3 is appropriate.

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 uses a specific verb ('Read') and identifies the resource ('metrics database'), clearly indicating this is a read operation for metrics. It distinguishes itself from mutation tools like inject and orchestrate, though it does not explicitly contrast with read-like siblings such as status or logs.

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 is given about when to use this tool versus alternatives like status or logs. The description only states what it does, not the context in which it should be selected.

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

orchestrateB

Orchestrate a complex task: decompose, inject subtasks, monitor, return results

ParametersJSON Schema
NameRequiredDescriptionDefault
waitNoWait for completion
assertionsNo
auto_startNoAuto-start coordinator
descriptionYesHigh-level task to orchestrate
timeout_secondsNoMax wait time

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only gives high-level steps without disclosing whether execution blocks (wait param), how failures are handled, or if there are side effects. The description omits key behavioral details like async behavior and results structure.

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 a clear action verb and a concise list of capabilities. It is front-loaded and contains no wasteful words.

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?

This is a complex orchestration tool with 5 parameters and no output schema, but the description fails to explain return value structure, error handling, or how assertions and timeout factor in. It is insufficient for an agent to invoke correctly.

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 high (80%), so baseline is 3. The description does not add meaning beyond the schema; the parameter details are left to the schema, which already covers most parameters.

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 orchestrates a complex task and lists specific capabilities (decompose, inject subtasks, monitor, return results), which distinguishes it from siblings like metrics or assert.

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 use for complex tasks require decomposition and monitoring, but it does not explicitly state when to use this tool versus alternatives like coordinator or inject, 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.

statusA

Get live status: coordinator, queue counts, workers

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.5/5.0
Behavior2/5

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

No annotations exist, so the description carries the burden. It only lists the content ('coordinator, queue counts, workers') but doesn't disclose any behavioral traits such as read-only nature, response format, or potential side effects, leaving ambiguity.

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—single sentence, front-loaded with the essential verb and resource. Every word earns its place with no redundancy.

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 zero-param, no-output-schema tool, the description is minimal but adequate. However, it lacks any detail about response structure or when to use it, so it's not fully complete for an agent to predict behavior.

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

Parameters4/5

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

The tool has zero parameters, so the baseline is 4. The description adds no parameter-level detail, but none is needed since there is nothing to configure.

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's purpose: 'Get live status: coordinator, queue counts, workers'. It uses a specific verb and resource and distinguishes itself from sibling tools like metrics and logs by focusing on current operational state.

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 is provided on when to use this tool versus alternatives. It doesn't mention exclusions or context, leaving the agent to infer when 'status' is appropriate compared to 'metrics' or 'logs'.

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. 8 tool updatesv1.0.0
    • First observedassert
    • First observedcoordinator
    • First observedhandle_stuck
    • First observedinject
    • First observedlogs
    • First observedmetrics
    • First observedorchestrate
    • First observedstatus

TDQS

B3.3/5.0
Disambiguation4/5

Tools are mostly distinct: metrics, status, and logs each read different data sources (DB, live coordinator state, files), while inject, orchestrate, handle_stuck, and coordinator manage different aspects of the system. However, metrics and status could be confused for overlapping system information.

Naming Consistency2/5

Tool names mix nouns (metrics, status, logs, coordinator) with imperative verbs (inject, handle_stuck, orchestrate, assert). There is no consistent verb_noun or noun_verb pattern, making the set feel ad hoc.

Tool Count5/5

Eight tools is well within the ideal 3-15 range for this domain. Each tool serves a distinct operational purpose without redundancy or bloat.

Completeness4/5

The set covers core operations: observability (metrics, status, logs), task injection, failure recovery, coordinator control, high-level orchestration, and assertion. Minor gaps exist (e.g., no direct task result retrieval outside orchestrate), but workflows are largely complete.

Maintenance

ActivityStale
ResponsivenessNo issues

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