Planning
AWS LabsOfficialPublished by AWS Labs
- Skill
- Meta (authoring, orchestration, planning, memory)
- Agent tooling
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The planning skill acts as the central orchestrator for model customization projects. It translates user intent into a structured, step-by-step plan, ensuring that all necessary prerequisites are met and that workflows are logically ordered. By maintaining a persistent PLAN.md file, it tracks task status and manages transitions between specialized skills, ensuring that complex processes like fine-tuning or model evaluation are executed in a controlled and transparent manner.
What it does
- Interprets user goals to identify required model customization steps.
- Generates a structured, numbered task list for project execution.
- Manages the lifecycle of a project plan, including creation, iteration, and status tracking.
- Enforces prerequisite dependencies between different agent skills.
- Surfaces potential constraints and limitations based on user decisions.
- Coordinates hand-offs between specialized skills during task execution.
When to use it
- At the start of any model customization project, including fine-tuning or training.
- When you need to evaluate a base model before committing to further customization.
- When you need to resume, modify, or continue an existing project plan.
- When you require a clear, step-by-step roadmap for complex AI development tasks.
Advantages
- Ensures all technical prerequisites are satisfied before execution.
- Provides clear visibility into project progress and remaining tasks.
- Prevents common errors by enforcing logical task ordering.
- Allows for flexible plan adjustments based on user feedback or changing requirements.
Usage examples
- “I want to fine-tune a model for my customer support chatbot.”
- The agent will initiate the planning process, ask whether you prefer an evaluate-first or direct fine-tuning workflow, and generate a structured plan.
- “I have already evaluated the base model and want to start fine-tuning now.”
- The agent will recognize the intent to skip evaluation, load the direct fine-tuning plan, and present the relevant steps for your approval.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/awslabs/planning/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip planning.zip -d .agents/skills
Documentation by AWS Labs
Principles
One question at a time. Each question should resolve a branching decision in the plan. Avoid generic or out-of-domain questions.
Surface constraints early. If a user decision would constrain downstream options, flag it before the plan is finalized.
Keep plans short. Only include tasks that are necessary for the user's stated goal.
Don't ask what you already know. Check conversation history and project files before asking the user.
Phase 1: Brainstorming
Goal: Understand what the user wants to accomplish and identify which skills belong in the plan.
Read references/input-output-contracts.md, references/model-customization-plan.md, and references/evaluate-first-plan.md to:
Identify which skills could be relevant to the user's stated goal.
Check whether the user has the necessary input artifacts for each skill. If not, find the skills that generate those inputs and add them first.
Order skills to allow a smooth transition from one to the next and avoid dead ends.
Check if a recommended workflow matches the user's needs. If not, assess what modifications are needed and verify they are possible against the contracts table.
Decide which skills in a matching workflow can be skipped.
Surface limitations early — if a user decision (model choice, region, evaluation method) would constrain downstream options, mention it proactively, get user feedback, and adapt the plan accordingly.
During brainstorming:
Workflow choice gate: Before generating any plan, determine whether the user wants the evaluate-first workflow or the direct fine-tuning workflow. If the user has explicitly chosen (e.g., "evaluate first", "skip evaluation", "already evaluated the base model"), proceed with their choice. Otherwise, present both options with brief pros/cons and ask the user to choose. Saying "fine-tune" or naming a technique alone is NOT an explicit choice to skip evaluation — the user may not know evaluate-first is an option. Do NOT present a plan until the user has chosen a path. After they choose, read ONLY the corresponding reference plan.
Use the Restrictions column of the contracts table to flag constraints as soon as the relevant decision is made. Examples (non-comprehensive list, check contracts table for the full picture):
User picks a Nova model → alert that deployment regions are limited.
User picks a region → alert if it conflicts with model availability.
If a restriction applies, check whether it requires changes to other steps in the plan.
Do NOT ask the user about base model selection or preferences. Model selection is handled exclusively by the
model-selectionskill.Move to Phase 2 as soon as you can determine which skills and tools the plan needs.
Phase 2: Plan Generation
Goal: Propose a structured plan for the user to review.
Generate a plan as a numbered list of tasks. Each task has:
A short name
A one-sentence description of what happens
Which skill handles it (if applicable)
Format:
Based on what you've described, here's what I propose:
1. ⬜ **[Task Name]** — [What happens]. *(Skill: [skill-name])*
2. ⬜ **[Task Name]** — [What happens]. *(Skill: [skill-name])*
3. ⬜ **[Task Name]** — [What happens]. *(Skill: [skill-name])*
Does this plan look right, or would you like to change anything?Rules for plan generation:
Infer ordering from the Prerequisites column in the contracts table — a skill cannot appear before its prerequisites. If unsure, consult
references/skill-routing-constraints.md.Only offer capabilities covered by an available skill. If the user needs something no skill supports, say so.
Tailor the plan to the user's actual intent. Not every plan needs every skill.
If the user already has input artifacts (e.g., a trained model), skip the steps that produce them.
When the user approves the plan, write it to PLAN.md and save it under the project directory structure defined by the directory-management skill.
# Plan
1. ⬜ **[Task Name]** — [Description]. _(Skill: [skill-name])_
2. ⬜ **[Task Name]** — [Description]. _(Skill: [skill-name])_
3. ⬜ **[Task Name]** — [Description]. _(Skill: [skill-name])_Status indicators:
⬜ Not Started
🔄 In Progress
✅ Completed
Update PLAN.md whenever a task's status changes.
Phase 3: Plan Iteration
Goal: Refine the plan until the user approves it.
If the user suggests changes, regenerate the plan incorporating their feedback.
If the user approves, begin execution by handing off to the first task's skill.
Execution
Once the plan is approved:
Before starting a task, update its status in
PLAN.mdto 🔄 (In Progress).If the task maps to a skill, load that skill's full SKILL.md before doing any work. Do not attempt the task from general knowledge — always defer to the skill's instructions.
Execute the task by following the loaded skill's workflow.
When the task completes:
Update its status in
PLAN.mdto ✅ (Completed). If the task generated output files (scripts, notebooks, manifests), record the file paths under the completed task:- [x] Fine-tune model - Output: `scripts/01_sft_finetuning.py` - Output: `manifests/sft-llama-20260515.json`Briefly confirm completion and move to the next task.
If the user interrupts with a new request mid-execution:
Completed tasks are immutable — do NOT modify them.
Regenerate the remaining tasks to incorporate the user's new input.
Present the updated remainder for approval before continuing.
Plan Completion
When all tasks in the plan are done: Present to the user:
"We've completed everything in the plan. What would you like to do next?"
This re-enters Phase 1 (Brainstorming) for a new goal. There is no terminal state — the conversation continues as long as the user wants.
References
Load the reference plan that matches the customer's intent, then adjust based on their needs.
references/evaluate-first-plan.md— The evaluate-first workflow: evaluate a base model before deciding whether to fine-tune.references/model-customization-plan.md— The direct fine-tuning plan. Use when the user has explicitly committed to fine-tuning.references/input-output-contracts.md- A table showing all skills, required inputs, produced outputs, prerequisites, and constraints.references/skill-routing-constraints.md— Optional supplemental resource about Mandatory inclusion rules, ordering constraints, and skill boundary rules.
Files
- ATTRIBUTION.mdAdded by AutoGineer900 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer89 B
- SKILL.md7.2 KiB
- references/evaluate-first-plan.md1.8 KiB
- references/input-output-contracts.md6.3 KiB
- references/model-customization-plan.md1.5 KiB
- references/skill-routing-constraints.md2.3 KiB
LICENSE
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- AWS Labs
- Publisher
- AWS Labs (Official)
- Source
- awslabs/agent-plugins · plugins/sagemaker-ai/skills/planning · commit fbefb37
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by AWS Labs or AWS Labs.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download planning.zip