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/beeline-migration)<a href="https://agentmods.dev/skills/honeycombio/agent-skill/beeline-migration"><img src="https://agentmods.dev/badge/skills/honeycombio/agent-skill/beeline-migration.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 | $0.00151 | $0.01196 |
| Opus 5 | $0.00076 | $0.00598 |
| Sonnet 5 | $0.00030 | $0.00239 |
| Haiku 4.5 | $0.00015 | $0.00120 |
Grade A, and why
beeline-migration 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.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Beeline to OpenTelemetry Migration
Step-by-step guide for migrating from Honeycomb Beelines (now End of Life) to OpenTelemetry instrumentation.
Status
Honeycomb Beelines have reached End of Life and are archived. All new instrumentation should use OpenTelemetry. Existing Beeline users should migrate as soon as practical.
Migration Strategy
Migration follows a two-phase approach that allows incremental, service-by-service migration without breaking distributed traces.
Phase 1: Enable W3C Trace Propagation (All Services)
Before migrating any service to OTel, all services must support W3C trace headers. This enables Beeline and OTel services to share trace context.
- Upgrade each Beeline to the minimum version supporting W3C headers
- Configure each Beeline to use W3C propagation format
- Deploy all services with W3C enabled
- Verify: Traces still link correctly across services
Minimum Beeline versions for W3C support:
| Language | Minimum Version |
|---|---|
| Go | 1.4.0 |
| Java | 1.7.0 |
| Node.js | 3.2.2 |
| Python | 2.18.0 |
| Ruby | 2.8.0 |
Phase 2: Migrate Each Service to OTel (One at a Time)
After all services support W3C headers:
- Choose a service to migrate (start with leaf services — fewest dependencies)
- Replace Beeline SDK with OpenTelemetry SDK
- Configure OTLP exporter to point to Honeycomb
- Add auto-instrumentation libraries
- Replicate any custom Beeline instrumentation in OTel
- Deploy and verify traces still connect
- Repeat for next service
Key rule: Complete Phase 1 across ALL services before starting Phase 2 on ANY service.
W3C Propagation Configuration
Go Beeline
beeline.Init(beeline.Config{
HTTPPropagationHook: propagation.W3C,
})
Python Beeline
beeline.init(
http_trace_propagation_hook=beeline.propagation.w3c.http_trace_propagation_hook,
http_trace_parser_hook=beeline.propagation.w3c.http_trace_parser_hook,
)
What ships with it
2 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.
- 6d ago First seen · 124 lines · 151 tokens per session scan A 35776c68a4ad
beeline-migration is a skill published in the GitHub repository honeycombio/agent-skill (22 stars, last pushed 9d ago), licensed MIT. It adds 151 tokens to every session and 1,196 once invoked, about $0.0008 per session on Opus 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
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…
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…