Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mhrsdev/AI-Agent-Skills-Library --skill decision-mappinggit clone --depth 1 https://github.com/mhrsdev/AI-Agent-Skills-LibraryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mhrsdev/ai-agent-skills-library/decision-mapping)<a href="https://agentmods.dev/skills/mhrsdev/ai-agent-skills-library/decision-mapping"><img src="https://agentmods.dev/badge/skills/mhrsdev/ai-agent-skills-library/decision-mapping/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mhrsdev/ai-agent-skills-library/decision-mapping"><img src="https://agentmods.dev/badge/skills/mhrsdev/ai-agent-skills-library/decision-mapping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.00814 |
| Opus 5 | $0.00014 | $0.00407 |
| Sonnet 5 | $0.00005 | $0.00163 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
decision-mapping scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to decision-mapping — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This skill is invoked when a loose idea requires more than one agent session to turn into a plan. It creates a stateful decision map in a markdown file, and drives the user through a sequence of tickets to resolve the open questions - which may require either prototyping, research or discussion.
The Decision Map
The decision map is a single compact Markdown file, one per planning effort, git-tracked alongside the project. It is the canonical artifact — the whole map is loaded as context into every session, so it must stay compact.
Assets created during tickets should be linked to from the map, not duplicated within it.
Structure
Numbered entries ("tickets"), each its own section keyed by its number:
## #1: Relational Or Non-Relational Database?
Blocked by: #<ticket-number>, #<ticket-number>
Type: Research | Prototype | Grilling
### Question
<question-here>
### Answer
<answer-here>
Each ticket must be sized to one 100K token agent session.
Ticket Types
There are three types of tickets:
- Research: Reading documentation, third-party API's, or local resources like knowledge bases. Creates a markdown summary as an asset. Use this when knowledge outside the current working directory is required.
- Prototype: Writing UI or logic code to test a hypothesis, or to explore a design space. Uses the /prototype skill. Creates a prototype as an asset. Use this when "how should it look" or "how should it behave" is the key question.
- Grilling: Conversation with the agent. Uses the /grilling and /domain-modeling skills. Asks one question at a time. The default case.
Fog of war
The map is deliberately incomplete beyond the frontier. Your job is to investigate the frontier, and to resolve tickets in order to push the frontier forward. Push back the fog of war, one node at a time.
At some point, the fog of war should have been pushed back far enough that the path to the finish line is clear. At that point, no more tickets will be required and the decision map can be considered 'done'.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 85 lines · 27 tokens per session scan A d71faf119fb6
decision-mapping is a skill published in the GitHub repository mhrsdev/AI-Agent-Skills-Library (6 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 814 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to decision-mapping, differing in 8 lines, and is treated as a copy.
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