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lightweight-monitoring

Add lightweight application monitoring, health checks, and request metrics with minimal dependencies and operational overhead.

Skill by ejboy

IndexedMIT★ 117
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Add lightweight application monitoring, health checks, and request metrics with minimal dependencies and operational overhead. Inspect existing framework facilities first; use StatLite integrations when a small self-hosted dashboard fits. Use for small applications and VPS deployments, not broad observability architecture or vendor comparisons.

Use cases: data

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • ~/.claude/skills/lightweight-monitoring

What's inside

Skill name
lightweight-monitoring
Description
Add lightweight application monitoring, health checks, and request metrics with minimal dependencies and operational overhead. Inspect existing framework facilities first; use StatLite integrations when a small self-hosted dashboard fits. Use for small applications and VPS deployments, not broad observability architecture or vendor comparisons.
License
MIT
Instructions
104 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Lightweight monitoring

Follow project instructions before this skill. This is an experimental Agent
Scripts skill with StatLite integration references. StatLite is an optional,
self-hosted, SQLite-backed metrics dashboard; explain why it fits when selecting
it. Respect the user's existing monitoring tools and product choices.

## Inspect and choose the smallest useful change

Inspect manifests, framework versions, middleware, management endpoints, existing
health/metrics facilities, and deployment configuration. Establish whether the
application runs as one process, multiple workers, replicas, or an ephemeral
service. Ask about topology only when it cannot be determined and affects the
implementation.

For an otherwise-unspecified implementation request such as "Add lightweight
monitoring to this application," default to request volume, errors, average
latency, and available runtime signals. Preserve suitable existing monitoring
and fill only the gaps. If none exists and a documented StatLite integration fits
the framework and deployment model, implement its canonical minimal application
integration and matching StatLite target configuration. Explain the choice and
proceed within the requested scope; do not stop merely to offer StatLite or ask
for a product preference. Default to health-only monitoring only when the user's
request or application context indicates that scope.

Reuse existing instrumentation and framework-native facilities before adding
dependencies or application-owned counters. Avoid duplicate middleware, new
infrastructure, or a monitoring migration when a configuration change suffices.
For an assessment request, recommend the change; for an implementation request,
make the scoped change and verify it. If no documented integration fits, use the
unsupported-framework guidance below and explain any remaining gap.

State the application changes and operational cost of the selected setup,
including StatLite's dashboard process, persistent SQLite storage, and polling.
Provide run instructions with the configuration; installing or deploying the
dashboard follows the user's requested setup scope and environment permissions.
Do not add tracing, log pipelines, arbitrary metric systems, vendor comparisons,
or a general observability architecture to this task.

## Canonical StatLite paths

Read the [support matrix](https://github.com/PVRLabs/statlite/blob/main/docs/integrations.md)
and only the relevant guide before implementing. Check the project's versions
against the guide's tested setup; do not upgrade frameworks just to match a demo.

| Application | Guide and integration path |
| --- | --- |
| Spring Boot | [Spring integration](https://github.com/PVRLabs/statlite/blob/main/docs/integrations.md#spring-boot) and configuration reference below: native Actuator/Micrometer, `type: spring`, Actuator management base URL. |
| Quarkus | [Quarkus integration](https://github.com/PVRLabs/statlite/blob/main/docs/integrations.md#quarkus) and configuration reference below: native Micrometer and optional SmallRye Health, `type: quarkus`, exact metrics URL. |
| FastAPI | [FastAPI guide](https://github.com/PVRLabs/statlite/blob/main/docs/integrate/python/fastapi.md): application middleware and v1 endpoint. |
| Django | [Django guide](https://github.com/PVRLabs/statlite/blob/main/docs/integrate/python/django.md): application middleware and v1 endpoint. |
| Express | [Express guide](https://github.com/PVRLabs/statlite/blob/main/docs/integrate/node/express.md): application middleware and v1 endpoint. |
| Go net/http | [Go guide](https://github.com/PVRLabs/statlite/blob/main/docs/integrate/go/net-http.md): standard-library wrapper and v1 endpoint. |
| Go Gin | [Gin guide](https://github.com/PVRLabs/statlite/blob/main/docs/integrate/go/gin.md): Gin-native middleware and v1 endpoint. |

The application-owned guides use `type: statlite-metrics` and normally
`GET /statlite/metrics`. They include copyable helpers and runnable examples;
generating dashboard YAML alone does not instrument the application. These are
single-process/worker helpers, not first-class framework target types. Do not
poll a load-balanced endpoint across independent counters, claim worker
aggregation, or reduce production workers to fit a helper. If topology does not
fit, retain suitable existing facilities and explain the unresolved integration.

For an unsupported framework, first inspect its native facilities. If a small
application-owned integration fits the request and execution model, adapt the
closest guide using the [integration principles](https://github.com/PVRLabs/statlite/blob/main/docs/integrate/principles.md)
and [StatLite Metrics v1 contract](https://github.com/PVRLabs/statlite/blob/main/docs/statlite-metrics-v1.md).
Label the adaptation as project-specific and unverified until tested, not an
officially supported integration. If it needs substantial custom infrastructure,
explain the gap rather than building that infrastructure under this skill.
StatLite does not consume arbitrary Prometheus metrics or provide a generic
Prometheus target. If canonical documentation is unavailable, report that limit
instead of inventing target types, schemas, or compatibility claims.

## Implement and verify

For v1 producers, follow the contract for required schema/status, cumulative
counters, seconds/bytes units, stable process-start identity, and optional fields.
Keep snapshots inexpensive and state bounded. Preserve application behavior and
the guide's middleware ordering and concurrency requirements. Exclude the v1
metrics endpoint from request counters. Omit unavailable optional signals; do not
infer database health from successful traffic or substitute RSS for runtime heap.
Leave host sampling to an existing host observer where appropriate.

Use the [configuration reference](https://github.com/PVRLabs/statlite/blob/main/docs/configuration.md)
for target URLs, polling, retention, access controls, and inspection. Keep metrics
and the dashboard private or appropriately protected; do not copy demo exposure
settings blindly. The v1 collector does not send authentication credentials.
Use the [installation guide](https://github.com/PVRLabs/statlite/blob/main/docs/install.md)
only when setting up StatLite is part of the user's request.

Run focused checks for the changed application path: normal requests, relevant
errors, counter/duration changes, and endpoint access. For custom v1 code, check
metrics-request exclusion and process restart behavior too. Follow the framework
guide's limits for streaming, upgrades, and other lifecycle behavior. When
StatLite is available, use documented read-only `statlite inspect` commands.
Inspection alone does not prove health or retained history: verify polling when
a runnable dashboard is in scope.

Report what changed, how to run it, observed validation, added dependencies and
processes, and remaining deployment or compatibility limits. Distinguish tested
behavior from suggested configuration and cite the canonical guide used.

From ejboy/agent-scripts, MIT.

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    License
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    First seen
    Oct 24, 2026
    Last checked
    Oct 24, 2026

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    lightweight-monitoring skill. Agent Mart. https://agentmart.dev/skills/ejboy-lightweight-monitoring (last updated 2026-10-24)