Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/cyanheads/openalex-mcp-server/api-telemetrynpx skills add cyanheads/openalex-mcp-server --skill api-telemetrygit clone --depth 1 https://github.com/cyanheads/openalex-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cyanheads/openalex-mcp-server/api-telemetry)<a href="https://agentmods.dev/skills/cyanheads/openalex-mcp-server/api-telemetry"><img src="https://agentmods.dev/badge/skills/cyanheads/openalex-mcp-server/api-telemetry.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00085 | $0.04958 |
| Opus 5 | $0.00043 | $0.02479 |
| Sonnet 5 | $0.00017 | $0.00992 |
| Haiku 4.5 | $0.00009 | $0.00496 |
Grade A, and why
api-telemetry scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to api-telemetry — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
The framework auto-instruments every tool, resource, prompt, storage, LLM, speech, and graph call — each gets its own span and the standard counters/histograms. HTTP server requests pick up spans from HttpInstrumentation (all Node.js HTTP traffic, skips /healthz) plus httpInstrumentationMiddleware from @hono/otel on the MCP HTTP endpoint when installed (optional Tier 3 peer — bun add @hono/otel). On Bun, HttpInstrumentation silently no-ops and @hono/otel is the only HTTP coverage. Auth checks and session lifecycle are tracked as metrics only — auth decorates the active HTTP span with attributes, sessions emit counters.
requestId, traceId, and tenantId correlate automatically across spans, metrics, and logs. Pino logs get trace_id/span_id injected when a span is active.
A handler's ctx.traceId / ctx.spanId name the execution span it runs in — tool_execution:<name> or resource_read:<name> — not the enclosing HTTP request span. Under HTTP the trace ID is the request's, so handler logs join to the request; the span ID is the child execution's, so they join to that span's attributes and duration. On stdio, where no transport span exists, both are still populated from the execution span the framework opens. Both are undefined when telemetry is disabled: the non-recording span a disabled pipeline produces carries all-zero IDs, and the framework reports no correlation rather than IDs that correlate to nothing.
For the helper API surface (withSpan, createCounter, createHistogram, buildTraceparent, etc.) — see the api-utils skill, Telemetry section. This skill is the catalog of what is emitted; that one is the reference for how to emit your own.
Enabling export
OTel is off by default. OTEL_ENABLED=true alone does nothing — you also need an OTLP endpoint. Without an endpoint the SDK is configured but nothing leaves the process.
| Env var | Default | Purpose |
|---|---|---|
OTEL_ENABLED |
false |
Master switch. Must be true to start the SDK. |
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT |
— | OTLP/HTTP traces endpoint (e.g. http://localhost:4318/v1/traces). |
OTEL_EXPORTER_OTLP_METRICS_ENDPOINT |
— | OTLP/HTTP metrics endpoint (e.g. http://localhost:4318/v1/metrics). |
OTEL_SERVICE_NAME |
createApp name → package.json name |
service.name resource attribute. Seeded from createApp({ name }) when unset; an env value wins. |
OTEL_SERVICE_VERSION |
package.json version |
service.version resource attribute. |
OTEL_TRACES_SAMPLER_ARG |
1.0 |
Trace sampling ratio (0–1) for TraceIdRatioBasedSampler. |
OTEL_LOG_LEVEL |
INFO |
OTel diagnostic logger level (NONE/ERROR/WARN/INFO/DEBUG/VERBOSE/ALL). |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 253 lines · 85 tokens per session scan A bb656e39dd17
api-telemetry is a skill published in the GitHub repository cyanheads/openalex-mcp-server (14 stars, last pushed 2d ago), licensed Apache-2.0. It adds 85 tokens to every session and 4,958 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to api-telemetry, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
patsnap-patent-literature-search
Search Patsnap's global patent and scientific literature databases together using natural-language, semantic, keyword, and BM25-based queries with multidimensional filters, then fetch patent or literature records as Markdown.
opik-diagnose
Surface the Opik traces worth a developer's attention, ranked by signal — errors, failed tool calls, latency, regressions, and low online-eval scores — plus Diagnostics issues. Reads live/production traces via the SDK (searchtraces and agentinsights) and works with no MCP; uses the MCP issue entity when connected.…
cortex-explore-memory
Explore the memory system's state, find gaps in knowledge, assess coverage, and get diagnostic information. Use when the user asks 'what does my memory look like', 'show me memory stats', 'what am I missing', 'how good is my knowledge', 'memory health', 'show coverage', 'find gaps', 'what topics are weak', or when you…
qmclaw-workbench
使用 OpenQuantum 的 QMClaw Local Tool 对超导量子比特 S21、能谱、Rabi、Ramsey、T1、SingleShot、DRAG、π 脉冲、功率偏移、Delta 和 RB 等 13 类测控实验做有界、确定性的本地模拟,并组织单比特调校工作流。用于实验规划、接口联调、教学和无硬件预检;不连接 LabRAD/lqms、真实仪器或量子云,不修改校准参数,也不替代 Scientific Validator。.
quick-capture
Use this skill to drop a new task into GSD Task Manager from any AI assistant that has the gsd-mcp-server connected.
xmemo-vscode
Use XMemo from VS Code (and forks like Cursor/Windsurf) to recall project context, capture engineering decisions, preserve handoff state, and connect to the hosted XMemo MCP endpoint safely.