Monitors Blender rendering processes, detects thermal spikes, and provides tools to throttle or manage Blender workloads to prevent crashes.
Sends rich, color-coded alerts via Discord webhooks for team-wide render farm monitoring.
Monitors Houdini simulations and provides thermal status and emergency throttling capabilities.
Sends private production pager-style notifications via Telegram bot when system thresholds are exceeded.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Frame Pulse MCP check system health before starting a render"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
in progress
AI-native telemetry for creative workstations.
Give your AI assistant (Claude, Hermes, Cursor) a "nervous system" to monitor and govern heavy creative workloads—Blender renders, Unreal builds, Houdini simulations—preventing thermal crashes and lost work during crunch.
Digital content creation (DCC) tools are resource-intensive. During overnight renders or UE5 lighting builds, workstations overheat, hang, or crash—destroying hours of work and missing deadlines.
Existing tools (Glances, htop) show data. Frame Pulse lets AI act.
Traditional Monitoring | Frame Pulse with AI |
You watch numbers | Claude asks "Is my system safe?" |
Crash after the fact | Throttle before thermal damage |
Manual Task Manager | Natural language "deprioritize Chrome" |
Silent failure | Discord/Telegram alerts at 2AM |
Related MCP server: DivLens MCP
Clone and install
git clone [https://github.com/idaakiwumi/frame-pulse-mcp.git](https://github.com/idaakiwumi/frame-pulse-mcp.git)
cd frame-pulse-mcp
pip install -r requirements.txtAdd to Claude Desktop config
Windows (MSIX/Store): %LOCALAPPDATA%\Packages\Claude_pzs8sxrjxfjjc\LocalCache\Roaming\Claude\claude_desktop_config.json
**Other possible paths
\AppData\Roaming\Claude\claude_desktop_config.json
\AppData\Local\Claude\claude_desktop_config.json
Standard: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"frame-pulse": {
"command": "py",
"args": [
"-3.14",
"-u",
"C:\\Users\\YOUR_PATH\\frame-pulse-mcp\\src\\frame_pulse\\server.py"
]
}
}
}Then ask Claude: "Check my system status" or "Deprioritize my background apps"
I built a high-fidelity Mission Control Dashboard using Streamlit. While the MCP runs in the background, this dashboard serves as the visual command center for the project.
streamlit run streamlit_app/mission_control.pyAs a Product Architect, I designed Frame Pulse to be "Headless." Creative professionals don't want another window to monitor; they want an assistant that pings them when they are away from their desk.
Telegram Bot: Acts as a private production pager. Get a message on your phone if your CPU hits 90°C while you're grabbing coffee.
Discord Webhooks: Rich, color-coded embeds sent to your studio's Discord server for team-wide render farm monitoring.
Setup: Configure your .env file with your TELEGRAM_BOT_TOKEN and TELEGRAM_CHAT_ID.
Tool | Function | Use Case |
| CPU, RAM, and Thermal scan | "Is it safe to start a 6-hour render?" |
| Identifies Blender, Unreal, Maya, etc. | "What's currently taxing the GPU?" |
| Immediate CPU priority reduction | "CRITICAL: Throttle background apps now." |
| Real-time temperature read | "Am I at risk of a thermal shutdown?" |
**Featured on Lobehub — AI tools discovery platform.
MCP — Model Context Protocol for AI tool interoperability
FastMCP — Python SDK for MCP servers
psutil — Cross-platform system monitoring
Streamlit — Rapid Python dashboarding
[30-second GIF: Claude asking "Start my render?" → Frame Pulse responding "CAUTION: CPU 89%" → User clicking throttle → Success toast]
"Frame Pulse caught a thermal spike before our overnight farm render. Saved us 14 hours of redo work."
— Anonymous VFX Supervisor (via DM)
If this tool saved your render from thermal throttling, prevented a 3AM crash, or helped your AI agent make hardware-aware decisions—consider fueling continued development:
Lead Product Designer | Creative Technologist | Narrative Strategist
Translating user friction into product opportunities.
Check if workstation is safe for heavy creative workloads.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 disclosure. It states the tool 'checks' safety but does not explain what criteria define 'safe', what internal operations occur (e.g., reading sensors), or whether the tool has side effects. This is insufficient for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the basic purpose. It is front-loaded and efficient, though it could be expanded slightly without losing conciseness. Score 4 for being appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of parameters and output schema, the description should provide more context on expected output format or interpretation (e.g., returns true/false or a status). The agent is left unsure what 'safe' means or what the tool returns, making it less complete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100% (empty schema). No additional parameter documentation is needed, so the description does not need to add parameter meaning. Baseline score of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks workstation safety for heavy creative workloads. It uses a specific verb and resource, and the sibling tools list suggests this is a diagnostic tool, distinguishing it from action-oriented tools like throttle_process or prioritize_process.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when assessing readiness for heavy workloads, but it does not provide explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. Some inference is possible from sibling names, but no explicit advice is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
SAME AS THROTTLE — reduces CPU priority of a process.
Use this if "throttle" sounds too aggressive. Same function, clearer language.
Args: target_pid: Process ID to deprioritize. If None, auto-selects highest CPU consumer.
Returns: Confirmation with full explanation of effects.
| Name | Required | Description | Default |
|---|---|---|---|
| target_pid | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the core action (reducing CPU priority) and auto-selection behavior when target_pid is None. However, it does not mention error handling, permission requirements, or reversibility, leaving some behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: three short sentences plus structured args/returns. It front-loads the core purpose and usage guideline, and every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description covers the core effect, auto-selection, and return type. It could add more on side effects or permissions, but given the low complexity, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter's schema has 0% description coverage, so the description must compensate. It explains 'target_pid' as the process ID to deprioritize and specifies that None auto-selects the highest CPU consumer, adding critical meaning beyond the basic type definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reduces CPU priority of a process, with a specific verb ('reduces') and resource ('process'). It also distinguishes itself from the sibling 'throttle_process' by explaining it is the same function with clearer language.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool instead of 'throttle' ('Use this if throttle sounds too aggressive'), providing clear context for choosing between aliases. It does not cover comparisons with other siblings like 'prioritize_process', but the guidance is direct and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Alias for throttle_process.
| Name | Required | Description | Default |
|---|---|---|---|
| target_pid | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must explain behavior. It only says it's an alias, offering no disclosure of what throttling entails, side effects, or safety profile. This is severely deficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (4 words), but this is under-specification rather than conciseness. It lacks essential information that could be added without verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and one parameter, the description is woefully incomplete. It does not explain the purpose, effect, or return value, leaving the agent with no actionable information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not mention the 'target_pid' parameter or explain how to use it. The schema alone (integer or null) is insufficient for an agent to know what PID to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description reads 'Alias for throttle_process,' which is a tautology. It does not state what the tool actually does (e.g., throttles a process). It fails to distinguish from sibling tools like emergency_throttle_process.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this alias versus the original throttle_process or emergency variants. The description lacks any context about appropriate scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
EMERGENCY: Immediately reduce priority without confirmation.
Use when:
System in CRITICAL thermal state (CPU >90%, Temp >85°C)
Render farm node about to shut down from overheating
No time for explanation
Returns: Action taken, minimal explanation.
| Name | Required | Description | Default |
|---|---|---|---|
| target_pid | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the no-confirmation behavior and minimal return explanation, but lacks details on reversibility or what 'reduce priority' entails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with three sentences and bullet points. No wasted words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool and no output schema, the description is incomplete because it omits any explanation of the input parameter, which is essential for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not explain the sole parameter 'target_pid', which is optional with null default. The agent lacks guidance on what the parameter does.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Immediately reduce priority without confirmation', specifying both the verb (reduce priority) and resource (process). The emergency context distinguishes it from sibling tools like 'throttle_process' and 'deprioritize_process'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists conditions for use (critical thermal state, no time) but does not mention when not to use or contrast with sibling tools like 'throttle_process'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Alias for scan_creative_apps.
| Name | Required | Description | Default |
|---|---|---|---|
| app_name | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is limited to stating it is an alias. No behavioral traits (e.g., idempotency, side effects) are disclosed beyond the reference to the sibling, which is insufficient for a tool that likely performs an action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one short sentence), but it omits essential information, making it under-specified rather than genuinely concise. Every sentence should earn its place; this one does not provide standalone value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema, no annotations, and one undocumented parameter, the description should provide substantial context. It fails to do so, leaving the agent unable to understand what the tool does or how to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds no meaning to the single parameter 'app_name'. The agent has no clue what this parameter does or how to use it. Baseline would be 3 with full coverage, but here description must compensate and fails completely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Alias for scan_creative_apps,' which implies the tool performs the same function as that sibling. However, it does not independently describe what the tool does, relying entirely on the sibling's definition. This is vague without external context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 alias versus the original scan_creative_apps or other sibling tools like emergency_throttle_process. The agent has no basis to choose this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Alias for check_system_health.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose any behavioral traits like side effects, permissions, or whether it is read-only. The term 'alias' implies equivalence but lacks explicit detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence), but it is under-specified. It lacks important context about the tool's functionality, making it insufficient rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, and no annotations, the description should provide more context about what the operation does. It merely references another tool, leaving the agent without a clear understanding of the behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and the input schema is complete with 100% coverage. The description adds no parameter information, which is acceptable but not helpful. Baseline for 0 params with high schema coverage is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description simply states it's an alias for 'check_system_health', but does not explain what that tool does. This is vague and requires the agent to look up another definition to understand the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 its siblings, such as 'emergency_throttle_alias' or 'check_system_health'. The description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Give a process HIGHER than normal CPU priority.
WARNING: Use sparingly. High priority can make system unresponsive.
Use only when:
A critical render must finish by deadline
System is otherwise idle
You accept risk of temporary unresponsiveness
Args: target_pid: Process ID to boost (REQUIRED)
Returns: Confirmation with warning about side effects.
| Name | Required | Description | Default |
|---|---|---|---|
| target_pid | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description warns of unresponsiveness and advises sparing use. Could specify priority level or required privileges, but overall adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise: three lines purpose, then structured warning and usage conditions. Front-loaded and no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, parameters, side effects, and return value. Complete for a single-parameter tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Target_pid is explained as 'Process ID to boost (REQUIRED).' Schema only gives type, so description adds needed context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Give a process HIGHER than normal CPU priority.' Specific verb+resource, and distinct from siblings like deprioritize_process and throttle_process.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists three conditions for use: critical render deadline, system idle, and acceptance of risk. Also warns against frequent use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Restore a throttled process to normal CPU priority.
Use this to 'undo' a throttle/deprioritize if you throttled the wrong process or if your main render finished and you want full performance back.
Args: target_pid: Process ID to restore to normal priority (REQUIRED, no auto-detect for safety)
Returns: Confirmation of priority restoration.
| Name | Required | Description | Default |
|---|---|---|---|
| target_pid | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral context beyond the missing annotations by stating the action (restore priority) and safety constraint (no auto-detect, required PID). It discloses that it returns a confirmation, though lacks detail on errors or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is brief with only three sentences covering purpose, usage, and parameter details. No unnecessary words, and information is front-loaded in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a minimal return statement. However, the tool's simplicity and context from sibling tools make it adequately complete for an agent to understand and use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description explains the parameter 'target_pid' as the process ID to restore, emphasizing it is required and that auto-detect is disabled for safety, adding meaning beyond the integer type in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it restores a throttled process to normal CPU priority, using the verb 'restore' and specifying 'normal CPU priority'. It distinguishes itself from siblings like 'throttle_process' and 'prioritize_process' by focusing on undoing a throttle.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly mentions when to use this tool: to undo a throttle/deprioritize if the wrong process was throttled or after a render finishes. This provides clear context and helps the agent decide between this and similar tools like 'prioritize_process'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find active creative applications (Blender, Unreal, Maya, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| app_name | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It only states the action without disclosing whether the operation is read-only, what side effects occur, authentication requirements, or rate limits. The lack of any behavioral context beyond 'Find' leaves the agent uncertain about impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately conveys the tool's purpose. Every word is necessary and no redundant information is present. It is optimally concise for its simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single optional parameter and no output schema, the description should explain what happens when app_name is omitted or provided, what the output format is, and whether it returns real-time data or cached. The lack of these details makes the tool incomplete for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 the single parameter 'app_name'. While the description lists example applications, it does not clarify that the parameter is used to filter results. The agent cannot infer the parameter's purpose or syntax from the description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Find active creative applications') and provides examples (Blender, Unreal, Maya) that distinguish it from sibling tools like find_render_processes_alias or check_system_health. The verb-resource combination 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.
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. It does not mention prerequisites, exclusions, or context in which a sibling tool would be more appropriate. For a scanning tool among many process-related tools, this is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Reduce CPU priority of a process to prevent overheating.
ALIASES: Also responds to "deprioritize" for clarity.
Args: target_pid: Process ID to throttle. If None, auto-throttles highest CPU consumer.
Returns: Confirmation message with explanation of what was done.
| Name | Required | Description | Default |
|---|---|---|---|
| target_pid | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the behavioral trait of reducing CPU priority and auto-selection, but does not mention potential side effects, reversibility, or permission requirements. This is adequate but lacks depth for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: three sentences and an aliases note. It front-loads the purpose, followed by aliases and parameter details. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers input behavior, default action, and return format (confirmation). It could mention response structure or error cases, but is sufficient for this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by explaining that target_pid defaults to None and when None, it auto-throttles the highest CPU consumer. This compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Reduce CPU priority of a process to prevent overheating', specifying the verb, resource, and goal. It distinguishes from siblings like prioritize_process by focusing on reduction and overheating prevention, and mentions auto-selection of highest CPU consumer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reducing CPU priority to prevent overheating, and explains that omitting target_pid auto-throttles the top CPU consumer. However, it does not explicitly state when to use this tool over siblings like deprioritize_process or prioritize_process, nor does it provide when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0check_system_healthdeprioritize_processemergency_throttle_aliasemergency_throttle_processfind_render_processes_aliasget_thermal_status_aliasprioritize_processrestore_priorityscan_creative_appsthrottle_processMultiple tools are aliases or near-duplicates (e.g., throttle_process, deprioritize_process, emergency_throttle_alias, emergency_throttle_process), making it hard for an agent to distinguish between them without careful reading. Similarly, find_render_processes_alias duplicates scan_creative_apps, and get_thermal_status_alias duplicates check_system_health.
Tool names use a mix of verbs like check, deprioritize, emergency_throttle, find, get, prioritize, restore, scan, throttle with no consistent pattern. The inclusion of '_alias' suffixes alongside action-oriented names adds inconsistency.
The total of 10 tools is within the normal range, but nearly half are redundant aliases, making the set feel bloated. The actual distinct functionality is only 5 operations, suggesting the tool count could be streamlined.
Core operations for CPU priority management are covered (health check, app scanning, throttle/deprioritize, emergency throttle, restore, boost). However, missing generic process listing and ability to set arbitrary priority values are minor gaps that could affect some workflows.
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Connect, monitor, and control AI agents — tasks, approvals, schedules, and governance.
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