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Decision Map

Community
Mathews-Tom
decision-map

Maps the unresolved architecture, policy, and scope decisions that must be answered before planning can start: one durable decision ticket per question on the issue tracker, typed and blocker-linked under a parent map, with fog-of-war, out-of-scope, a computed frontier, and one decision resolved per invocation. Triggers on: "map the decisions", "what do we need to decide", "identify the unknowns", "not ready to plan yet", "decision map", "chart this effort", "work the next decision ticket", "wayfinder". Use when the destination is still uncertain. NOT for implementation slices of a known feature, use task-decomposer. NOT for milestone plans, use plan-prompts.

Overview

PublisherMathews-Tom
Repositoryarmory
Skill namedecision-map
Stars
318
Forks
47
Bundled files
12
LicenseMIT
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.

  • 12 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Mathews-Tom on GitHub. Read the source before you install it.

Installation

Install the Decision Map 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.
  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/Mathews-Tom/armory.git /tmp/armory
mkdir -p .claude/skills
cp -r /tmp/armory/skills/decision-map .claude/skills/decision-map
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Decision Map 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 Decision Map 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 Decision Map 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.

Decision Map

Scope and Trigger Boundary

Ask one discriminator before creating anything: Do we know what should be built? If no, map unresolved decisions. If yes, route known design into milestones with plan-prompts or implementation-sized work with task-decomposer. A decision map produces decisions and evidence, never implementation deliverables.

SituationPackage
Destination or design still unclear; decisions would have to be inventeddecision-map
Design known; needs milestones and execution promptsplan-prompts
Feature specified; needs implementation slices, tests, riskstask-decomposer
Plan exists; needs a pre-implementation auditplan-review
Plan approved; needs execution across sessionsmilestone-runner
Repo audit needs standalone remediation plans, optionally as issuescodebase-advisor --issues
One decision needs a durable recordadr-writer
Session state must survive a handoffhandoff

Do not turn vague hopes into implementation tasks merely to make progress appear orderly. A sharp but currently unanswered question is a ticket. A question that cannot yet be stated sharply is fog.

Data Model

A map is one parent tracker item with five sections: Destination, Notes, Decisions so far, Not yet specified, and Out of scope. It is an index, not a duplicate store. A decision exists in exactly one ticket; the map holds only resolution pointers and scope boundaries.

A ticket holds one question, exactly one type label, exactly one interaction label, blockers, visible owner, session claim, and closure state. Refer to maps and tickets by linked title, never a bare identifier. Type labels are decision-map:discussion, decision-map:research, decision-map:prototype, and decision-map:unblock. Interaction labels are authoritative: exactly one of decision-map:hitl or decision-map:afk; ticket bodies must not restate the interaction mode.

Prerequisites

Use gh --version and require gh 2.96.0 or newer only when the user explicitly selects GitHub as the tracker. Verify authentication with gh auth status before that path. frontier.py requires Python 3.12 and only the standard library. .docs/agents/issue-tracker.md, when present, is the authoritative backend choice. Otherwise store maps locally in .docs/decision-maps/<effort>/; select GitHub only when the user expressly asks for it. Do not infer GitHub selection from a remote or authentication. Report the selected backend once and mention project-context-setup when the choice should be persisted. Probe GitHub capability before using native relationships. When older GitHub Enterprise or an older CLI rejects blockedBy, take the degraded path: generated child links in the map and Blocked by: #N lines in ticket bodies. The degraded index exists only to emulate absent tracker relationships.

Workflow

Mode A — Chart the Map

  1. Name the destination before discussing its route. Use one concrete either-or question at a time and reuse the effort's vocabulary.
  2. Sweep breadth-first for policy, architecture, scope, evidence, access, and design questions. If no fog surfaces, stop: the effort needs no decision map.
  3. Ensure labels and the selected backend schema exist. Create the map with all five sections.
  4. Create every question already sharp enough to ticket. Give every ticket exactly one type label and exactly one interaction label.
  5. Wire blocker edges only after ticket creation, because the backend needs ticket identifiers before it can connect them.
  6. Put the remaining unformulated uncertainty in Not yet specified; record conscious exclusions with a reason in Out of scope.
  7. Compute the frontier and map state with frontier.py; report created topology and stop.

Charting resolves nothing, runs no research, implements nothing, and never collapses uncertainty to look tidy. Report the AFK-ready frontier separately: those tickets may be advanced by that many independent work invocations, each resolving at most one ticket.

Mode B — Work Through the Map

  1. Load only the map body, select the requested frontier ticket or the first item returned by frontier.py, and establish visible ownership.
  2. Acquire and verify the session claim before substantive work. Follow references/claim-protocol.md; do not infer exclusivity from assignment.
  3. Resolve exactly one ticket by its type. A HITL ticket requires the human's judgment; an agent answering it alone has broken the ticket.
  4. Record one closure path: RESOLVED, OUT_OF_SCOPE, or INVALIDATED. Write the decision or evidence in the ticket, close it with the matching backend path, and add only a pointer in Decisions so far or Out of scope.
  5. Create newly surfaced sharp questions, graduate them out of fog, and remove only the graduated fog patch. Recompute frontier and state.
  6. Report and stop without selecting another ticket.

unblock work is restricted to evidence, access, measurement, setup, or a minimal experiment that makes a decision answerable. It never implements a product feature.

Output

Chart Output

Report map title and identifier, tickets with type and interaction labels, blocker edges, current frontier, remaining fog, computed map state, and the stop condition. Include the AFK-ready frontier count and state that each item requires a separate work invocation.

Work Output

Report the resolved ticket, closure path, recorded decision or evidence, new tickets, changed blocker edges, resulting frontier, state, and stop condition. When the state is COMPLETE, recommend plan-prompts for implementation planning. Do not create an inline plan.

Claim Protocol

Visible ownership and session claim are separate requirements. On GitHub, a claim comment begins with decision-map claim, includes session: and claimed-at:, and is re-read before work. The lowest non-stale database comment identifier, encoded in the issue-comment URL, wins. A loser withdraws, removes its assignee if it added one, recomputes the frontier, and selects another ticket. A claim older than the map's configured TTL, default 24 hours, can be preempted with a recorded reason.

Local maps use an exclusive claims lock. See references/claim-protocol.md for exact arbitration, stale-claim, and release rules.

Map States

An empty frontier does not mean completion. Evaluate the ordered ladder: actionable unclaimed ticket means ACTIVE; otherwise any claimed open ticket means WAITING; otherwise any open ticket means BLOCKED; otherwise non-empty fog means FOGGY; otherwise no open tickets, no fog, and no Unresolved contradiction: entry in Notes means COMPLETE.

Error Handling and Troubleshooting

FailureDiagnoseCorrective action
Tracker document absentinspect .docs/agents/issue-tracker.mduse the local .docs/decision-maps/ backend unless the user selected GitHub
Native relationship unsupportedgh issue view <map> --json blockedByuse degraded generated links and body blockers
Label schema absentgh label listbootstrap labels idempotently before ticket creation
Two sessions claim one ticketre-read comments and database comment identifierslowest fresh identifier wins; loser withdraws
Claim belongs to dead sessioncompare timestamp to map TTLrecord preemption, then claim
Empty frontier with open ticketsrun frontier.pyreport WAITING or BLOCKED, never complete
Map and tickets driftinspect map pointers and backend graphrepair generated degraded index or resolution pointers
Malformed local claim lockinspect the lock contentsstop; preserve it for diagnosis rather than overwriting it

Fail loudly when the map label is absent, a ticket has missing or multiple type or interaction labels, the capability probe is ambiguous, or claim verification fails. Do not silently create a replacement map.

Rationalizations

Reject these statements:

  • “I'll resolve two; they are small.” One invocation resolves one ticket.
  • “I'll pre-slice fog while I am here.” Fog is deliberately not a task list.
  • “I know the answer, so no human is needed.” That violates a HITL ticket.
  • “I'll just build it; it is faster.” Implementation is outside this package.
  • “The frontier is empty, so we are done.” The state ladder decides that.

Red Flags

Bare issue numbers in narration, maps that repeat ticket content, sharp questions left in fog, closed tickets without resolution comments, scope boundaries listed as decisions, or substantive work before claim verification all signal a broken map.

Verification

Confirm all five map sections exist; every open ticket is a child of the map and has exactly one type and interaction label; every blocker edge is native or documented as degraded; ownership and claim were verified before substantive action; each closure used one valid path and reached the correct map section; and the reported state matches frontier.py.

bash
uv run python skills/decision-map/scripts/frontier.py --map 42
uv run python skills/decision-map/scripts/frontier.py --map 42 --degraded
uv run python skills/decision-map/scripts/frontier.py --local .docs/decision-maps/billing

References

ReferencePurpose
references/map-format.mdMap schema, template, and index rules
references/ticket-types.mdTypes, labels, and closure boundaries
references/claim-protocol.mdGitHub arbitration and local exclusion
references/map-states.mdOrdered state ladder
references/tracker-operations.mdGitHub, degraded, and local backend operations
references/elicitation.mdDiscovery questions and vocabulary discipline
references/research-resolution.mdSelf-contained AFK research protocol
scripts/frontier.pyNormalized frontier and state computation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Decision Map AI skill do?

Maps the unresolved architecture, policy, and scope decisions that must be answered before planning can start: one durable decision ticket per question on the issue tracker, typed and blocker-linked under a parent map, with fog-of-war, out-of-scope, a computed frontier, and one decision resolved per invocation. Triggers on: "map the decisions", "what do we need to decide", "identify the unknowns", "not ready to plan yet", "decision map", "chart this effort", "work the next decision ticket", "wayfinder". Use when the destination is still uncertain. NOT for implementation slices of a known fe...

Why use Decision Map on TypingMind?

Because you install it once and use it with any model. Decision Map 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 Decision Map in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Mathews-Tom/armory/tree/main/skills/decision-map. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Decision Map?

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 Decision Map?

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

Is the Decision Map AI skill free?

Yes. It is published on GitHub by Mathews-Tom under the MIT license. 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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