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 skills add Consensys/ask-o11y-plugin --skill querying-profilesgit clone --depth 1 https://github.com/Consensys/ask-o11y-pluginWrote 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/consensys/ask-o11y-plugin/querying-profiles)<a href="https://agentmods.dev/skills/consensys/ask-o11y-plugin/querying-profiles"><img src="https://agentmods.dev/badge/skills/consensys/ask-o11y-plugin/querying-profiles/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/consensys/ask-o11y-plugin/querying-profiles"><img src="https://agentmods.dev/badge/skills/consensys/ask-o11y-plugin/querying-profiles.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00079 | $0.00704 |
| Opus 5.5 | $0.00032 | $0.00282 |
| Sonnet 5.5 | $0.00016 | $0.00141 |
| Haiku 4.5 | $0.00008 | $0.00070 |
Grade A, and why
querying-profiles 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile query workflow
- Identify the datasource UID — every Pyroscope tool requires
data_source_uid(the plugin's configured Pyroscope datasource). - Discover profile types — List available profile types with
list_pyroscope_profile_typesto confirm what this instance collects (CPU, memory, goroutines, mutex, block). - Discover labels and values — Use label discovery tools to enumerate label names (
service_name,env,namespace, ...) and verify concrete values exist before filtering. - Run the profile query — Call
query_pyroscopewith:profile_type— confirmed in step 2matchers— label selectors, e.g.{service_name="payments", env="prod"}(comma-separatedkey="value"pairs inside braces)query_type—profile(flamegraph data),metrics(time-series of the same profile), orboth(default; one call, complete analysis)format—table(default) for the per-function flat/cumulative table, ordotfor a Graphviz call graphgroup_by— labels to group themetricsseries by (e.g.service_name)
- Read the flame graph — flat (self) vs cumulative interpretation below.
- Compare windows — for regressions, diff the same profile type before/after a deploy or peak vs baseline; deltas localize the offending function.
Profile types and symptoms
| Symptom | Profile type |
|---|---|
| High CPU | process_cpu:cpu:nanoseconds:cpu:nanoseconds |
| OOM / memory growth | memory:inuse_space:bytes:space:bytes |
| GC pressure / allocation churn | memory:alloc_space:bytes:space:bytes |
| Hung/slow goroutines | goroutine:goroutine:count:: |
| Lock contention | mutex:contentions:count:: |
See references/profile-types.md for the full taxonomy, symptom→type mapping, and flame-graph reading guide.
Interpreting results
- Flat time = time in the function itself; cumulative includes callees
- Wide flat blocks at branch tips are where work happens; wide low blocks are subtrees to zoom into
- High latency with a flat CPU flame graph means waiting (I/O, locks), not computing — switch to
mutex/blockprofiles or correlate with traces
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed · +8 lines · +14 tokens per session 1eefaec08115
- 1mo ago First seen · 41 lines · 65 tokens per session scan A a0003ab53aec
querying-profiles is a skill published in the GitHub repository Consensys/ask-o11y-plugin (42 stars, last pushed 1mo ago), licensed MIT. It adds 79 tokens to every session and 704 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-07.
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