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Invest Remediate

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erikaflowers
invest-remediate

Read an AUDIT.md and generate a phased remediation plan — a sequence of self-contained, agent-executable prompts ordered from lowest-risk to highest-risk. Each phase is scoped to be completable in one session.

Overview

Publishererikaflowers
Repositoryinvestiture
Skill nameinvest-remediate
Stars
55
Forks
9
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by erikaflowers on GitHub. Read the source before you install it.

Installation

Install the Invest Remediate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/erikaflowers/investiture/tree/main/.claude/skills/invest-remediate
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/erikaflowers/investiture.git /tmp/investiture
mkdir -p .claude/skills
cp -r /tmp/investiture/.claude/skills/invest-remediate .claude/skills/invest-remediate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Invest Remediate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Invest Remediate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Invest Remediate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Remediation Plan Generator

You read an audit report and produce a phased remediation plan. Each phase is a self-contained prompt that an agent (or human) can execute independently, in order, without needing to understand the whole audit.

Target

Read the audit at $ARGUMENTS. If no argument is provided, look for AUDIT.md in the current working directory.

Process

1. Parse the audit

Read AUDIT.md and extract:

  • Every finding (critical, significant, minor)
  • Every dead code entry
  • Every recommended remediation priority
  • The per-file classification table

2. Group findings into phases

Group findings into phases using these rules:

Phase ordering principle: lowest risk first, highest risk last.

Each phase should be:

  • Completable in one agent session (roughly 30-60 minutes of agent work)
  • Independent — completing phase N should not break anything that phase N+1 needs to find
  • Testable — there should be a way to verify the phase was done correctly

Standard phase order:

OrderCategoryRiskWhy this order
1Delete dead codeZeroRemoving unused files can't break anything. Reduces noise for subsequent phases.
2Fix naming & consistencyNear-zeroRenames and convention fixes. No behavior change.
3Add error boundaries / error handlingLowAdditive — wrapping existing code in safety nets doesn't change behavior.
4Add missing validation / security fixesLow-mediumTightening inputs. May surface bugs that were hidden by lax validation.
5Extract components / split monolithsMediumStructural refactoring. Same behavior, different organization. Tests should pass before and after.
6Performance fixesMediumMemoization, lazy loading, pagination. Behavior should be identical but faster.
7Architecture changesHighRedesigning data flow, splitting god files, changing state management patterns. Highest risk of regression.
8Feature completionVariableFinishing half-implemented features or removing stubs. Scope depends on the feature.

Not every audit will produce all 8 phase types. Skip phases that have no findings. Merge phases that are too small to justify a standalone session (e.g., if there's only one naming fix, fold it into dead code cleanup).

3. For each phase, generate a prompt

Each phase prompt must be self-contained. An agent receiving this prompt should be able to execute it without reading the original audit. The prompt must include:

Header:

## Phase [N]: [Title]
Risk: [zero | low | medium | high]
Estimated scope: [file count] files, [description of change type]
Prerequisite: [Phase N-1 completed, or "None"]

Context: 1-2 sentences explaining WHY this phase exists. What problem does it solve?

Tasks: Numbered list of specific changes. Each task must include:

  • The exact file path
  • What to do (delete, rename, extract, wrap, add, modify)
  • Line numbers or function names where applicable
  • What the result should look like (acceptance criteria)
  • What NOT to change (scope boundaries)

Verification: How to confirm the phase is complete:

  • Build still passes
  • Tests still pass (if tests exist)
  • Specific behavior unchanged
  • Specific files deleted / created / modified

Example phase prompt:

markdown
## Phase 1: Dead Code Cleanup
Risk: Zero
Estimated scope: 4 files, deletions only
Prerequisite: None

Remove files identified as unused in the audit. These files are not imported
by any other file and have been superseded by newer implementations.

### Tasks

1. **Delete** `src/components/KnowledgePanel.jsx` (140 lines)
   - Superseded by `src/pages/KnowledgePage.jsx`
   - Verify: grep the codebase for "KnowledgePanel" — should return 0 results after deletion

2. **Delete** `src/components/MemoryPanel.jsx` (155 lines)
   - Superseded by `src/pages/MemoriesPage.jsx`
   - Verify: grep for "MemoryPanel" — 0 results

3. **Delete** `src/labrador.css` (7348 lines)
   - Pre-refactor monolith. CSS was split into `src/css/*.css` files.
   - NOT imported by any file (verified: no import statements reference it)
   - Verify: `npm run build` still succeeds

4. **Delete** `.github/ISSUE_TEMPLATE/bug_report.md` and `.github/ISSUE_TEMPLATE/feature_request.md`
   - Superseded by `bug.yml` and `feature.yml` YAML form templates
   - Verify: remaining templates (`bug.yml`, `feature.yml`, `enhancement.yml`, `custom.md`, `config.yml`) still exist

### Verification
- [ ] `npm run build` passes (or equivalent build command)
- [ ] No new lint errors introduced
- [ ] Grep for deleted filenames returns 0 matches across codebase
- [ ] Net lines removed: ~7700

4. Write cross-phase notes

After all phases, include a section on:

  • Dependencies between phases — which phases must be done in order, which can be parallelized
  • Risk escalation — at what phase should the operator pause and verify before continuing
  • Bail points — phases where it's acceptable to stop and ship what's done so far

Output Format — REMEDIATION.md

Write the file at the same location as the audit (repo root by default).

markdown
# Remediation Plan

**Source:** AUDIT.md
**Generated:** [timestamp]
**Overall classification from audit:** [level]
**Total phases:** [N]
**Estimated total scope:** [file count] files across [phase count] phases

---

## Phase 1: [Title]
[full prompt as described above]

---

## Phase 2: [Title]
[full prompt]

---

[...continue for all phases...]

---

## Cross-Phase Notes

### Execution Order
[which phases are sequential vs parallelizable]

### Risk Checkpoints
[where the operator should pause and verify before continuing]

### Bail Points
[phases where it's safe to stop and ship partial remediation]

### What This Plan Does NOT Cover
[anything from the audit that was intentionally excluded — e.g., feature requests,
architectural opinions, or findings the auditor flagged as uncertain]

Rules

  • Every task must reference a specific file. No vague instructions like "improve error handling across the codebase." Instead: "Add try-catch to conversations.mjs handler body (lines 4-57) matching the pattern in cartridges.mjs (lines 70-75)."
  • Preserve the audit's commendations. If the audit says something is done well, the remediation plan should include a note: "Do NOT modify [thing] — it was flagged as well-implemented."
  • Don't invent findings. Only generate tasks for findings that appear in the audit. Do not add your own observations. If you notice something new while reading the audit, note it in "What This Plan Does NOT Cover."
  • Size phases for one session. A phase with 20 file changes is too large. Split it. A phase with 1 trivial change is too small. Merge it with an adjacent phase of similar risk level.
  • Include rollback guidance. For medium and high risk phases, note what to check if something breaks and how to revert (e.g., "If the build breaks after extracting ToolRegistry, revert the commit and check import paths").

Commit

When complete, save REMEDIATION.md and commit:

docs: phased remediation plan from audit

Frequently asked questions

What does the Invest Remediate AI skill do?

Read an AUDIT.md and generate a phased remediation plan — a sequence of self-contained, agent-executable prompts ordered from lowest-risk to highest-risk. Each phase is scoped to be completable in one session.

Why use Invest Remediate on TypingMind?

Because you install it once and use it with any model. Invest Remediate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Invest Remediate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/erikaflowers/investiture/tree/main/.claude/skills/invest-remediate. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Invest Remediate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Invest Remediate?

As many as you like. As long as a model supports skills, you can use Invest Remediate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Invest Remediate AI skill free?

It is published on GitHub by erikaflowers. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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