fix

fix is a command for coding agents from MarioEpkOne/PipelineIQ. It costs 0 tokens per session (1,191 once invoked), scanned A, original, MIT.

A targeted repair command that reads the listed errors from an implementation audit and addresses them.

In plain words
What is it for?
Use it after an audit to fix its actionable errors, either by audit name or by giving a file path.
Why use it?
It removes the need to manually find audit findings, gather their referenced files, and apply each correction.

Command

Part of the pipelineiq plugin — 10 commands, 6 agents shipped together

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.

agentmods
npx agentmods add commands/marioepkone/pipelineiq/fix
Clone the repo
git clone --depth 1 https://github.com/MarioEpkOne/PipelineIQ

Or install pipelineiq, the plugin that ships this one along with the rest of its 10 commands, 6 agents.

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 fix

README.md
[![agentmods](https://agentmods.dev/badge/commands/marioepkone/pipelineiq/fix.svg)](https://agentmods.dev/commands/marioepkone/pipelineiq/fix)
Your own site
<a href="https://agentmods.dev/commands/marioepkone/pipelineiq/fix"><img src="https://agentmods.dev/badge/commands/marioepkone/pipelineiq/fix.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,191 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01191
Opus 5 $0.00000 $0.00596
Sonnet 5 $0.00000 $0.00238
Haiku 4.5 $0.00000 $0.00119

Measured 5d ago against content hash 294c0d023755, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fix 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 5d 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.

commands/fix.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TARGETED FIX — reads an audit document's "Actionable Errors" section and fixes each error. Can be used standalone or invoked by the pipeline.

The user's request is: $ARGUMENTS


Phase 1 — Find Inputs

Search Working Logs/ for an audit document whose filename starts with audit-impl-- and contains the argument (case-insensitive).

  • If multiple matches: list them and ask the user to pick one.
  • If no match and argument looks like a file path: try reading it directly.
  • If no match: tell the user no audit found and exit.
  • If no argument: use the most recently modified file in Working Logs/ whose name starts with audit-impl--.

Read the audit document in full.

Parse the "Actionable Errors" section. If no such section exists: tell the user "This audit does not have a structured Actionable Errors section. Run /audit-implementation with the latest skill version to generate one." and exit.

From the audit header, read:

  • The referenced impl plan from Implementation Plans/
  • The referenced working log from Working Logs/ (if it exists)

Phase 2 — Read Context

For each actionable error entry, read every file listed in its File(s) field.

If the audit references a worktree in its header, resolve and use that worktree as the working root for file reads and edits.


Phase 3 — Fix Each Error

For each actionable error (skip entries under "Not actionable"):

  1. Read the relevant file(s) fresh (they may have changed since the audit)
  2. Apply the suggested fix using Edit/Write
  3. After each fix: verify no errors were introduced by running the project's build/lint/test command as appropriate
  4. If a fix introduces new errors:
    • Revert the change
    • Try a different approach (max 2 attempts per error)
    • If both attempts fail: mark as "fix failed" with explanation
  5. If the suggested fix doesn't apply (file changed, method renamed, etc.): mark as "deferred to user" with explanation

Log each fix result as you go — do not batch.


Read the full file on GitHub · 121 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. 5d ago First seen · 121 lines · 0 tokens per session scan A 294c0d023755

Subscribe to this mod's changes

fix is a command published in the GitHub repository MarioEpkOne/PipelineIQ (2 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,191 tokens. 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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