Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add honeycombio/agent-skill/plugin install honeycombWrote 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/honeycombio/agent-skill/query-patterns)<a href="https://agentmods.dev/skills/honeycombio/agent-skill/query-patterns"><img src="https://agentmods.dev/badge/skills/honeycombio/agent-skill/query-patterns/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/honeycombio/agent-skill/query-patterns"><img src="https://agentmods.dev/badge/skills/honeycombio/agent-skill/query-patterns.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 | $0.00131 | $0.01680 |
| Opus 5.5 | $0.00052 | $0.00672 |
| Sonnet 5.5 | $0.00026 | $0.00336 |
| Haiku 4.5 | $0.00013 | $0.00168 |
Grade A, and why
query-patterns 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 10d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Honeycomb Query Patterns
Opinionated guidance for writing effective Honeycomb queries. The MCP tools already document their parameters and schemas — this skill focuses on when and why to use each pattern, not how to call the tools.
Key Principles
- Never use AVG for latency — AVG hides tail latency. Use P99 (or P95/P90) to see what slow users experience. Reserve AVG for non-latency metrics like payload size.
- Use HEATMAP for distributions — Single-number aggregates hide bimodal patterns. HEATMAP reveals whether you have one population or two.
- Combine calculations in one query —
COUNT, P99(duration_ms), HEATMAP(duration_ms)in a single query reduces API calls and gives a complete picture. - Start broad, narrow with WHERE — Begin with a COUNT/GROUP BY to understand shape, then add filters to focus.
- Check for prior work — Call
find_queriesbefore writing new queries. Someone may have already answered the question.
Choosing the Right Operation
| Question | Use |
|---|---|
| How much traffic? | COUNT grouped by route or service |
| How many unique users/IPs? | COUNT_DISTINCT(field) |
| How fast for most users? | P50(duration_ms) |
| How fast for the worst-off users? | P99(duration_ms) |
| Is there a bimodal pattern? | HEATMAP(duration_ms) |
| What's the worst case? | MAX(duration_ms) |
| How many concurrent operations? | CONCURRENCY |
| Is it getting worse over time? | RATE_AVG(duration_ms) |
Relational Field Strategy
Use relational prefixes to ask cross-span questions within a trace:
- "Show me slow endpoints caused by a specific downstream": Filter with
any.service.nameto find traces where that service participates, group byroot.http.routeto see which user-facing endpoints are affected. - "What's different about errored traces?": Filter with
any.error = true, group byroot.nameto see which entry points have errors somewhere in their trace tree. - Exclude noise:
none.service.name = "health-check"removes traces containing health checks.
What ships with it
5 files 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.
- 10d ago Changed · -4 lines · -34 tokens per session f12650516007
- 1mo ago First seen · 113 lines · 165 tokens per session scan A e73cc391d9f8
query-patterns is a skill published in the GitHub repository honeycombio/agent-skill (28 stars, last pushed 10d ago), licensed MIT. It adds 131 tokens to every session and 1,680 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Optimize the meaningful UI available immediately from a Next.js route on an initial load (hard navigation) or named client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route and entry point at a time; the shipped test then guards…