Skip to main content
Glama

get_ping_instructions

Read-onlyIdempotent

After creating a monitor, get the ping URL, copy-paste check-in snippets, and reporting mechanisms. Choose the right method based on what you're monitoring, then start reporting.

Instructions

Get everything needed to make a monitor actually report: the ping URL, copy-paste check-in snippets, and the three MECHANISMS for reporting, returned together. Call this right after create_monitor. CHOOSE BY WHAT THE MONITORED THING IS — read reporting_options first and pick by that, rather than defaulting to the raw curl list: how_to — the manual protocol — is the UNIVERSAL path: it works in any agent, any language, any tool, with no prerequisite, so it is the default choice for any agent this applies to. Pair it with expect_every_s (the silence floor, set via update_monitor) so an agent that quietly stops reporting opens a detected incident instead of leaving its monitor reading healthy. If you ARE Claude Code specifically, hook_install is available as an OPTIONAL SHORTCUT, not a better tier: a one-time install that binds reporting to Claude Code's own hooks (UserPromptSubmit, Stop, StopFailure), automating how_to's exact same protocol so reporting becomes a property of your event loop instead of something you must remember — and it is the only mechanism that can send every state this product models, including blocked and note. hook_install is Claude Code specific: if you are a DIFFERENT AI agent — even one with its own hook or event system, Cursor, Windsurf, Codex, a custom framework — do NOT translate its steps into your own hooks; the event semantics differ and a translated install can pass its own verification while never reporting, so use how_to instead. If what you are monitoring is launched as a command instead — a cron job, a CI step, a script, or an agent started from a shell — use run_wrapper: wrap the command with lastping run and a separate process reports for you, so nothing has to be remembered; the tradeoff is that it reports the process's own lifecycle (start, success, fail, cancel) and has no way to send blocked or note. Whichever you choose, the underlying protocol is the same: the success ping at the END of the work, the fail URL if it failed, the start ping first for long or possibly-hung runs (this enables overrun / never-finished detection), and a step (curl_step) as each stage completes so a run that wedges mid-way is caught by name rather than only when its whole budget expires. Also read expectations_how_to: before you start work, use declare_run_expectations to say how THIS run should be judged when it closes — a one-time, unchangeable commitment that replaces the run grading itself. And discovery_how_to, which is about the OTHER jobs on this host or in this repo: how to find the scheduled work nobody is watching yet and propose it, rather than monitoring only the one thing you were asked about.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesMonitor UUID (from create_monitor or list_monitors).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to reassert safety. It adds meaningful behavioral context by explaining that the tool returns all mechanisms together, describes the universal protocol, and discloses the limitations of each mechanism (e.g., run_wrapper cannot send blocked or note). No contradiction with annotations exists.

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 front-loaded with the core purpose, and it has logical sections for choosing among mechanisms. However, it is very long and dense for a one-parameter getter, mixing returned-field descriptions, decision routing, protocol details, and follow-on tool guidance into continuous prose. Every sentence contributes useful content, but the structure could be tighter.

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

Completeness5/5

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

Because there is no output schema, the description carries the full burden of explaining what the tool returns and how to act on it. It covers all major return fields, names alternatives, gives prerequisites, warns about misuse, and connects to related tools like update_monitor and declare_run_expectations. An agent has enough context to select and invoke this tool 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?

There is only one parameter, id, and the schema already fully describes it as 'Monitor UUID (from create_monitor or list_monitors)'. The description adds no new parameter-specific semantics beyond implicitly reinforcing that the tool should be called after create_monitor, 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 opens with a specific verb and resource: 'Get everything needed to make a monitor actually report' and lists the concrete return contents: ping URL, copy-paste snippets, and three reporting mechanisms. It clearly differentiates this from siblings by framing it as the post-create_monitor retrieval of reporting setup material.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance ('Call this right after create_monitor'), names the three internal options, and provides strong exclusion rules: Claude Code may use hook_install, other agents must not translate it, and command-launched processes should use run_wrapper. It also tells the agent to read expectations_how_to and discovery_how_to, so the usage context is fully specified.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tp322d/lastping-app'

If you have feedback or need assistance with the MCP directory API, please join our Discord server