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 agentmods add skills/emergent-wisdom/understanding-graph/understanding-worknpx skills add emergent-wisdom/understanding-graph --skill understanding-workgit clone --depth 1 https://github.com/emergent-wisdom/understanding-graphWrote 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/emergent-wisdom/understanding-graph/understanding-work)<a href="https://agentmods.dev/skills/emergent-wisdom/understanding-graph/understanding-work"><img src="https://agentmods.dev/badge/skills/emergent-wisdom/understanding-graph/understanding-work.svg" alt="Measured on agentmods" 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 | $0.00105 | $0.02845 |
| Opus 5 | $0.00053 | $0.01422 |
| Sonnet 5 | $0.00021 | $0.00569 |
| Haiku 4.5 | $0.00011 | $0.00284 |
Grade A, and why
understanding-work 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Work through Understanding
Protocol compatibility: fluid-understanding-v1.
When this skill is active, the graph is the canonical medium in which the task develops. It is not a memory aid or filing cabinet visited after the answer is finished. The primary task is not merely to write a novel, answer a question, or produce code. It is to do that work through the Understanding Graph so the understanding that makes the artifact possible remains available for new work.
Do not wait for the user to name a tool. Begin in the graph unless the user explicitly asks not to use it. Chat may report progress, ask for a decision, or present a result; it does not replace graph work.
Maintain medium integrity: never leave newly developed substantive artifact text or communicable understanding only in chat. Before completing a turn, write the exact artifact units and genuine testimony to the graph. The final response may mirror or summarize what was committed. This is an invariant of the medium, not a mandatory sequence for how understanding must unfold.
Enter the medium
Call project_list before substantive graph work and confirm the active project
matches the task. If none is active, select an existing match or create a
descriptive, task-scoped one with project_switch; an empty list means create
one. If several existing projects are plausible, ask rather than guess. Never
create a generic catch-all project.
Choose the amount of navigation aid that suits the model and task:
- Direct: call
graph_understand,graph_batch, or another appropriate graph tool immediately and choose for yourself when to deepen, connect, test, revisit, disrupt, or pause. - Guided: call
graph_suggest_nextwhen graph-specific pointers could deepen or diversify understanding, recover neglected material, test the current view, or make a useful connection visible.
The live server may provide guided prompts automatically or run in direct mode.
Either way, graph_suggest_next remains optional and callable on demand. Its
weighted routes are provocations, not quality guarantees or required phases;
choose, combine, modify, reject, replace, or skip them. A route may call
graph_understand to bring task-relevant graph material into view. Treat any
returned material as provisional prior understanding, not authority. If the
graph is empty, begin honestly without inventing a past.
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.
- 5d ago First seen · 238 lines · 105 tokens per session scan A 4769013c8580
understanding-work is a skill published in the GitHub repository emergent-wisdom/understanding-graph (1 stars, last pushed 11d ago), licensed MIT. It adds 105 tokens to every session and 2,845 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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