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/resolve-ai-oss/resolve-ai-plugins/debug-integrationnpx skills add resolve-ai-oss/resolve-ai-plugins --skill debug-integrationgit clone --depth 1 https://github.com/resolve-ai-oss/resolve-ai-pluginsWrote 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/resolve-ai-oss/resolve-ai-plugins/debug-integration)<a href="https://agentmods.dev/skills/resolve-ai-oss/resolve-ai-plugins/debug-integration"><img src="https://agentmods.dev/badge/skills/resolve-ai-oss/resolve-ai-plugins/debug-integration.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 | $0.00099 | $0.00730 |
| Opus 5 | $0.00049 | $0.00365 |
| Sonnet 5 | $0.00020 | $0.00146 |
| Haiku 4.5 | $0.00010 | $0.00073 |
Grade A, and why
debug-integration 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 3d 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.
Debug a Resolve integration
Use when the user wants Resolve to diagnose or explain one of their integrations. The Resolve agent has internal tools to list integrations, load schema + redacted values + last health check + satellite scope, and (for satellite-backed integrations) read pod logs scoped to the right namespace.
This skill is read-only. To create or mutate integrations, see resolve-ai-admin:create-integration. To edit satellite Helm values, see resolve-ai-admin:satellite-configs.
Arguments
If $ARGUMENTS is non-empty, treat it as the user's question and proceed.
If $ARGUMENTS is empty (skill invoked without a clear question), ask the user once what's wrong with which integration. Treat their next reply as the base message.
Composing the ask
Compose one message for resolve-ai:ask. The agent will discover the target integration internally (list_integrations → get_integration_details) and invoke its own integration-debug skill to apply the diagnostic discipline (kubectl scoping rules, structured output formats).
You don't need to specify the integration instance id — describing the integration by name and symptom is sufficient. The agent will resolve which instance the user means.
Enrich the base message with conversation context that directly supports debugging this integration. Be ruthlessly selective:
- Error messages, log lines, or stack traces the user has shown that name the symptom
- Recent changes (deploys, config edits) that might be tied to the failure
- Health-check output the user pasted, if any
Format the enriched message as the user's question first, then a brief ## Local context block with only the relevant items. Hand that single composed message to resolve-ai:ask; it owns sending, scoping, streaming, and canvas URL handling.
After asking
Once resolve-ai:ask has produced its streamed or settled answer, expect a Mode A 4-block diagnosis (starts with **What's failing:** and includes Evidence / Likely cause / Suggested next step) when the user asked about a failure, or a Mode B field tour when they asked about config fields. Surface this verbatim — don't paraphrase the structured blocks.
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.
- 3d ago First seen · 49 lines · 99 tokens per session scan A 48ae7ac2c5d2
debug-integration is a skill published in the GitHub repository resolve-ai-oss/resolve-ai-plugins (4 stars, last pushed 9d ago), licensed Apache-2.0. It adds 99 tokens to every session and 730 once invoked, about $0.0005 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 2026-08-31.
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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
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