---
name: tackle-todos-fd56c547dd35
description: "Read TODO.md and scan source code for TODO/FIXME comments, build a consolidated list, then dispatch parallel agents to address as many items as possible."
user_invocable: true
allowed-tools: Bash, Read, Write, Edit, Grep, Glob, Agent
---

# Tackle TODOs: Consolidate and Resolve Open Items

This skill scans the project for all outstanding work items — both from `.agents/docs/TODO.md` and from `// TODO` / `// FIXME` comments in source code — builds a consolidated, deduplicated, prioritized list, and then dispatches parallel agents to resolve as many items as possible.

**Use this skill when:** you want to make a focused sweep of outstanding TODOs and fix them in bulk.

## Arguments

- `[filter]` (optional): A service name or keyword to restrict which TODOs to tackle (e.g., `dynamodb`, `iam`). If omitted, all TODOs are considered.

## Step 0: Collect TODOs from TODO.md

Read `.agents/docs/TODO.md` and extract every unchecked `- [ ]` item. Record its service, description, and source.

## Step 1: Scan Source Code for TODO/FIXME Comments

Use Grep to search `crates/` for `// TODO` and `// FIXME` patterns in `*.rs` files.

Group and deduplicate the results:
- Identical or near-identical comments (e.g., `// TODO: extract from httpResponseCode field` repeated 200+ times across wire.rs files) should be collapsed into a single work item with a note about which files/crates are affected.
- Comments that are informational-only (e.g., noting a known limitation that cannot be fixed without large design changes) should be flagged but deprioritized.

## Step 2: Build a Consolidated TODO List

Merge the two sources into a single list. Deduplicate items that appear in both TODO.md and as code comments.

For each item, assign a category:

| Category | Description | Priority |
|----------|-------------|----------|
| **systematic** | Same pattern repeated across many files (e.g., httpResponseCode extraction) | High — one fix propagates widely |
| **behavioural** | Missing AWS behaviour (e.g., ConditionExpression ignored, pagination missing) | High — affects correctness |
| **validation** | Missing input validation or error responses | Medium |
| **serialization** | Wire format or serialization bugs (e.g., XML list serialization) | Medium |
| **test-only** | TODO in test code noting a test gap, not a code defect | Low |
| **design** | Requires significant design work or new abstractions | Deferred — flag for user |

Write the consolidated list to `.agents-workspace/tmp/consolidated-todos.md` for reference.

## Step 2b: Verify stale items before dispatch

Before dispatching agents on any TODO entry that is more than 24 hours old, verify the entry is still applicable: grep the relevant code for the symptom ( the `json!` site, the lowercase enum literal, the missing handler, etc. ). Round 5 ( 2026-04-29 ) found multiple already-resolved entries ( `partiql-cleanup-orphans`, URL-decode audit sites ) that wasted agent time. Skip or close stale entries instead of dispatching.

## Step 3: Filter (if argument provided)

If the user passed a `[filter]` argument, restrict the work list to items matching that filter (service name, crate name, or keyword).

## Step 4: Plan Parallel Work Items

Group the consolidated TODOs into independent, parallelizable work units. Each work unit should:
- Be self-contained (touching one crate or one cross-cutting concern)
- Not conflict with other parallel work units (no two agents editing the same file)

Present the plan to the user and get confirmation before dispatching.

## Step 5: Dispatch Parallel Agents

For each approved work unit, launch an Agent (subagent_type: general-purpose) with a clear prompt that includes:

1. The specific TODO(s) to address
2. The files to modify
3. The expected behaviour (reference AWS documentation if needed)
4. Instructions to run the relevant integration tests after making changes (`cargo test -p winterbaume-{service} -- --no-fail-fast`)

Launch as many agents in parallel as there are independent work units. Each agent works in an isolated worktree to avoid conflicts.

Never use `isolation: worktree` for parallel agents, which have repeatedly caused troubles. Instead, launch tasks independent from one other in a batch.

## Step 6: Collect Results and Update TODO.md

After all agents complete:

1. Review each agent's results — check if the fix compiled and tests passed.
2. For successfully resolved items, mark them as `- [x]` in `.agents/docs/TODO.md` and remove the corresponding `// TODO` comments from source code.
3. For items that could not be resolved, add notes about why and what was attempted.
4. Append a summary to `.agents/docs/JOURNAL.md` documenting what was tackled and the outcomes.

## Notes

- **Do not attempt design-category items** without user approval. These require architectural decisions.
- **Systematic items** (like httpResponseCode extraction) are high-value because one code-generation or macro fix can eliminate hundreds of TODOs at once.
- Respect CLAUDE.md rules: no `git checkout`, no `git restore`, no discretionary commits. Agents should only edit files, not commit.
- When running tests, always use focused filters (`cargo test <pattern>`), `--test-threads=N`, or `--no-fail-fast`, and specific crate targeting (`-p winterbaume-{service}`). Note: `--maxfail` is a pytest flag, not a Rust libtest flag — do not pass it to cargo test.


---
Source attribution: moriyoshi
Original project: https://github.com/moriyoshi/winterbaume/blob/69fed1d7fb0eb9a2738ff3274197c7591129c4cb/.agents/skills/tackle-todos/SKILL.md
License: Apache-2.0
License information: https://www.apache.org/licenses/LICENSE-2.0
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice


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## Additional upstream notices

tackle-todos-fd56c547dd35/DAVEAI-UPSTREAM-NOTICE

Winterbaume
Copyright 2025 Winterbaume contributors

This product includes software developed at
https://github.com/getmoto/moto

=======================================================================
Moto - Mock AWS Services
=======================================================================

Copyright 2012 Steve Pulec

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Winterbaume used moto as a reference implementation for AWS service
mock behaviour and ported many of its Python test cases into Rust
integration tests. The moto source is available at
https://github.com/getmoto/moto.

Moto is written by Steve Pulec with contributions from:

  Zach Smith, Dilshod Tadjibaev, Dan Berglund, Lincoln de Sousa,
  mhock, Ilya Sukhanov, Lucian Branescu Mihaila,
  Konstantinos Koukopoulos, attili, JJ Zeng, Jon Haddad,
  Andres Riancho, Michael Ossareh, JeffMGreg, Hugo Lopes Tavares,
  Chris St. Pierre, Frank Mata, Clint Ecker, Richard Eames,
  Kevin Glisson, Shawn Falkner-Horine, David Baumgold,
  Rory-Finnegan, Bobby Impollonia, Ralfas, Omer Katz,
  Joseph Lawson, Trey Tacon, Peter, Tyler Sanders, Gary Dalton,
  Chris Henry, Mike Fuller, Andy, Mike Grima, Marco Rucci,
  Zack Kourouma, Pior Bastida, Dustin J. Mitchell,
  Jean-Baptiste Barth, Tom Viner, Justin Wiley, Adam Stauffer,
  Guy Templeton, Michael van Tellingen, Jessie Nadler,
  Alex Morken, Clive Li, Jim Shields, William Richard,
  Alex Casalboni, Jon Beilke, Bendeguz Acs, Craig Anderson,
  Robert Lewis, Kyle Jones, Mickaël Schoentgen, Ariel Beck,
  Roman Rader, Bryan Chen, Jonas Bulik, Rita Cheung,
  David Acevedo, Damon Williams

The full contributor list is available at
https://github.com/getmoto/moto/blob/master/AUTHORS.md.

=======================================================================
AWS API Models
=======================================================================

Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Winterbaume vendors a snapshot of the official AWS API Smithy models
under vendor/api-models-aws/ to drive its in-tree wire-type and
serialiser code generation. The upstream LICENSE and NOTICE files are
preserved alongside the vendored models. The upstream source is
available at https://github.com/aws/api-models-aws.


# Mega AI Hub resource metadata

Creator / publisher: moriyoshi
Original project: https://github.com/moriyoshi/winterbaume/blob/69fed1d7fb0eb9a2738ff3274197c7591129c4cb/.agents/skills/tackle-todos/SKILL.md
Attribution basis: Source repository record

Fields of work: Development & Engineering, Product Management
Roles: Backend Developer, DevOps / SRE, Product Manager
Specialties: Backend
Tools: Agent, Bash, Edit, Glob, Grep, Write
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 2d7b6fbf2be793a28c4efe8eade1df5c7f8624b5cb5760327dab0f2fbca40f32