pipeline-summary

pipeline-summary is a skill for Claude Code from TalonT-Org/AutoSkillit. It costs 32 tokens per session (1,295 once invoked), scanned A, original, MIT.

A reporting step that creates a GitHub issue and pull request summarizing bugs found and fixed during a pipeline run. A pipeline is an automated sequence that builds, tests, or checks code.

In plain words
What is it for?
It is for documenting accumulated pipeline bugs and opening a pull request from the feature branch to its target branch.
Why use it?
It preserves the history of pipeline problems and gathers the fixes into a reviewable change request.

Skill for Claude Code

Written for Claude Code: hooks in frontmatter.

Part of the autoskillit plugin — 121 skills, 1 MCP server shipped together

Good fit It is for documenting accumulated pipeline bugs and opening a pull request from the feature branch to its target branch.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/talont-org/autoskillit/pipeline-summary
Install

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.

Any agent
npx skills add TalonT-Org/AutoSkillit --skill pipeline-summary
Clone the repo
git clone --depth 1 https://github.com/TalonT-Org/AutoSkillit

Made for: Claude Code.

Or install autoskillit, the plugin that ships this one along with the rest of its 121 skills, 1 MCP server.

Wrote 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.

agentmods badge for pipeline-summary

README.md
[![agentmods](https://agentmods.dev/badge/skills/talont-org/autoskillit/pipeline-summary/github.svg)](https://agentmods.dev/skills/talont-org/autoskillit/pipeline-summary)
Your own site
<a href="https://agentmods.dev/skills/talont-org/autoskillit/pipeline-summary"><img src="https://agentmods.dev/badge/skills/talont-org/autoskillit/pipeline-summary/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.

agentmods 80×15 button for pipeline-summary

Your own site · 80×15
<a href="https://agentmods.dev/skills/talont-org/autoskillit/pipeline-summary"><img src="https://agentmods.dev/badge/skills/talont-org/autoskillit/pipeline-summary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,295 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.01295
Opus 5.5 $0.00013 $0.00518
Sonnet 5.5 $0.00006 $0.00259
Haiku 4.5 $0.00003 $0.00129

Measured 1mo ago against content hash 62297b56129a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pipeline-summary 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.

src/autoskillit/skills_extended/pipeline-summary/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pipeline Summary

Create a GitHub issue documenting bugs encountered during a pipeline run and a PR from the feature branch into the target branch.

Arguments

/autoskillit:pipeline-summary {bug_report_path} {feature_branch} {target_branch} {workspace} [{closing_issue}]

  • bug_report_path — Path to the JSON file containing bug metadata
  • feature_branch — Name of the branch containing all accumulated fixes
  • target_branch — Branch to create the PR against (e.g., "main")
  • workspace — Path to the git repository workspace
  • closing_issue — (Optional) GitHub issue number whose ## Requirements section should be extracted and embedded in the PR body. When absent or empty, requirements extraction is skipped.

When to Use

  • End of a pipeline run with collect_on_branch enabled
  • Any pipeline that accumulates fixes on a feature branch and needs a summary

Critical Constraints

NEVER:

  • Fail the pipeline if gh is not available or not authenticated — write a local summary instead
  • Create empty issues or PRs (skip if no bugs to report)
  • Modify any source code — this skill only creates GitHub artifacts and a summary file

ALWAYS:

  • Check gh auth status before attempting GitHub operations
  • Push the feature branch before creating the PR
  • Write a local summary markdown file regardless of GitHub availability
  • Output summary_path=<path> for capture by the orchestrator
  • If GitHub operations succeed, also output issue_url=<url> and pr_url=<url>

Workflow

Step 1: Parse Arguments

Parse up to five positional arguments from the prompt. The fifth (closing_issue) is optional.

Step 2: Read Bug Report

Read the JSON file at {bug_report_path}. Expected structure:

[
  {
    "step": "string — pipeline step where failure occurred",
    "error": "string — error description",
    "fix": "string — what was done to fix it",
    "iteration": "number — which bugfix iteration"
  }
]

If the file is empty, contains [], or doesn't exist, write a clean-run summary and exit successfully.

Read the full file on GitHub · 139 lines

Changes

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.

  1. 1mo ago First seen · 139 lines · 32 tokens per session scan A 62297b56129a

Subscribe to this mod's changes

pipeline-summary is a skill published in the GitHub repository TalonT-Org/AutoSkillit (5 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 1,295 once invoked, about $0.0001 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 2026-09-03.

Related

Other skills, from other repositories