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 orchestra-hq/orchestra-skills --skill fix-orchestra-pipelinegit clone --depth 1 https://github.com/orchestra-hq/orchestra-skillsWrote 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/orchestra-hq/orchestra-skills/fix-orchestra-pipeline)<a href="https://agentmods.dev/skills/orchestra-hq/orchestra-skills/fix-orchestra-pipeline"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/fix-orchestra-pipeline/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/orchestra-hq/orchestra-skills/fix-orchestra-pipeline"><img src="https://agentmods.dev/badge/skills/orchestra-hq/orchestra-skills/fix-orchestra-pipeline.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 | $0.00168 | $0.03406 |
| Opus 5.5 | $0.00067 | $0.01362 |
| Sonnet 5.5 | $0.00034 | $0.00681 |
| Haiku 4.5 | $0.00017 | $0.00341 |
Grade A, and why
fix-orchestra-pipeline 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 — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fix Orchestra Pipeline
Fix and retry an already-diagnosed Orchestra pipeline — and optionally remember what worked.
Prerequisites
This skill assumes the Orchestra MCP server is connected. All MCP calls are scoped to the user's workspace.
MCP tools
Use Orchestra MCP tools for all operations in this skill (read a pipeline's full definition with
get_pipeline). Argument summaries: ../../references/orchestra/mcp/tools-quick-ref.md.
Inputs from identify-pipeline-error
identify-pipeline-error is the entry point that parses the user's input (URL, UUID, alias, error
text, Slack alert), finds the failed run and task, and classifies the cause. It hands you:
- the pipeline run ID,
pipelineId,pipelineName,envName, runbranch/commit,triggeredBy - the failed task run(s):
id,taskName,taskId,integration,integrationJob,message,externalStatus,externalMessage,taskParameters,runParameters,connectionId,numberOfAttempts - the cause classification — an Orchestra-platform / configuration issue (or a repo-level fix in an integration with no dedicated skill).
Use these directly and proceed to Step 3. If invoked standalone (no handoff), run
identify-pipeline-error first to establish the failed run/task and the cause, then come back here.
Workflow overview
Execute these steps in order. Each step feeds the next.
Step 3 — Fetch diagnostics
Goal: Get the raw evidence — logs, artifacts, and operations.
For each failed task run:
-
Logs: Call
list_task_run_logsto list available log files. Then fetch each log withdownload_task_run_log. Focus on the last ~256KB of large logs usingrange_header(for examplebytes=-262144). -
Artifacts: Call
list_task_run_artifacts. For dbt tasks, look forrun_results.jsonandmanifest.json. Download relevant artifacts withdownload_task_run_artifact. -
Operations: Call
list_operationsfiltered bytask_run_idto see sub-operations (individual dbt models, Snowflake queries, etc.) and their statuses.
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 Changed · +5 lines 265cfa5e360f
- 1mo ago First seen · 307 lines · 168 tokens per session scan A 6a58407dd6c5
fix-orchestra-pipeline is a skill published in the GitHub repository orchestra-hq/orchestra-skills (9 stars, last pushed yesterday), licensed MIT. It adds 168 tokens to every session and 3,406 once invoked, about $0.0007 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 2026-09-09.
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