Agent skill

Decision Map

by Mathews-Tom in Mathews-Tom/armory

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…

MITAuto-check passedProduct & Project Management

Install Decision Map

skills CLI
$ npx skills add Mathews-Tom/armory --skill decision-map -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Mathews-Tom/armory decision-map --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/decision-map .claude/skills/decision-map && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
decision-map
GitHub stars
327
Token cost
~2.7k tokens
SKILL.md length
1,327 words
Files
20 (incl. scripts, references)
Skills in repo
80
Repo updated
First seen
Licence
MIT

At a glance

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…

  • Works in 7 steps: Name the destination before discussing… → Sweep breadth-first for policy,… → Ensure labels and the selected backend… → …
  • : map the decisions
  • SKILL.md covers Scope and Trigger Boundary, Data Model, Prerequisites and Workflow, plus 8 more sections
  • Runs Python scripts from its folder; calls gh and uv

What it does

Decision Map is an agent skill from Mathews-Tom/armory. 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…

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 25 other files, including scripts and reference files (for example `evals/cases.yaml`, `references/claim-protocol.md` and `references/elicitation.md`).

It sits in Product & Project Management, covering Project management and Issue triage. The repository describes itself as: Curated, production-grade skills for AI coding agents. Battle-tested workflows for developers who use AI seriously. The licence is MIT.

When your agent uses it

  • : map the decisions
  • What do we need to decide
  • Identify the unknowns
  • Not ready to plan yet

Example prompts

  • “map the decisions”
  • “what do we need to decide”
  • “identify the unknowns”
  • “/decision-map”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  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…
  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.

What it can do on your machine

Read from SKILL.md and the folder at commit 4594fb7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • gh
    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh and uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Decision Map loads about 2.7k tokens when it runs, and up to ~6k if it reads all its reference files. Until then it costs about 170 tokens; SKILL.md has 1,327 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~170
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Mathews-Tom/armory at commit 4594fb7, republished under its MIT licence (© Mathews-Tom). 1,327 words, ~2,735 tokens.

Download SKILL.mdSave it as .claude/skills/decision-map/SKILL.md (or your agent's skills folder). This skill also uses 19 other files; get the full folder from GitHub.
name
decision-map
description
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.
metadata.version
1.0.1
metadata.category
development
metadata.tags
planning, issue-tracker, decisions, discovery, frontier, pre-planning
metadata.difficulty
advanced
metadata.phase
define
metadata.complements
plan-prompts, task-decomposer, project-context-setup, adr-writer, plan-review

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.

Show full SKILL.md (520 more words)Show less

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

© Mathews-Tom, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 19 other files (scripts, references) in skills/decision-map of Mathews-Tom/armory.

  • SKILL.md
  • evals/cases.yaml
  • references/claim-protocol.md
  • references/elicitation.md
  • references/map-format.md
  • references/map-states.md
  • references/research-resolution.md
  • references/ticket-types.md
  • references/tracker-operations.md
  • references/upstream/LICENSE
  • references/upstream/provenance.md
  • scripts/frontier.py
  • tests/fixtures/github_issues.json
  • tests/fixtures/github_issues_degraded.json
  • tests/fixtures/local_map
  • … and 5 more

Open the folder on GitHubat commit 4594fb7

Compare with similar skills

Decision Map next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Decision Map compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Decision Map this skillMathews-Tom/armory327—~2.7kAutomated safety check: PassMIT
GitHub Project Management Swarmruvnet/agentic-flow8166 repos~7.1kAutomated safety check: PassNone
Issue Triagesuperset-sh/superset15k—~995Automated safety check: PassCustom licence
GitHub Issue Bulk Assignercodewhale-hq/Codewhale41k—~953Automated safety check: PassMIT
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
To Issuesywwynm/EverythingDone14412 repos~893Automated safety check: PassGPL-3.0

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Questions about Decision Map

What does Decision Map 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…. Decision Map is an agent skill from Mathews-Tom/armory. 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.

When should I use Decision Map?

Decision Map fits situations like: : map the decisions; what do we need to decide; identify the unknowns; not ready to plan yet.

How do I install Decision Map in Claude Code?

Run `npx skills add Mathews-Tom/armory --skill decision-map -a claude-code`. Or copy the skill folder (skills/decision-map in Mathews-Tom/armory) into .claude/skills/decision-map in your project. Claude Code loads it when a task matches its description.

How do I install Decision Map in Codex?

Run `npx skills add Mathews-Tom/armory --skill decision-map -a codex`. Or copy the skill folder (skills/decision-map in Mathews-Tom/armory) into .agents/skills/decision-map in your project. Codex loads it when a task matches its description.

Can I use Decision Map in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Mathews-Tom/armory --skill decision-map -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/decision-map, .gemini/skills/decision-map, .github/skills/decision-map and .opencode/skills/decision-map in your project.

What does Decision Map need to run?

Going by SKILL.md and its folder, Decision Map needs Python for the scripts in its folder and the command-line tools its instructions call (gh and uv). Our summary lists: Python 3.

Does Decision Map access the network?

SKILL.md contains no URLs. Its commands use gh and uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Decision Map safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Decision Map use?

Decision Map is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Decision Map use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.2k tokens, read only when the agent opens those files.

What are the alternatives to Decision Map?

Skills that share tags, products or a category with Decision Map: GitHub Project Management Swarm (ruvnet/agentic-flow, 816 stars), Issue Triage (superset-sh/superset, 15k stars), GitHub Issue Bulk Assigner (codewhale-hq/Codewhale, 41k stars) and CCPM Project Management (automazeio/ccpm, 8.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Decision Map?

Mathews-Tom (a GitHub user) maintains it in Mathews-Tom/armory, which has 327 GitHub stars. The repository holds 80 skills in this directory. The repository was last updated on October 6, 2026.

Source: Mathews-Tom/armory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.