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 agents/nomarj/sigil/agent-experience-mappergit clone --depth 1 https://github.com/NOMARJ/sigilWrote 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/agents/nomarj/sigil/agent-experience-mapper)<a href="https://agentmods.dev/agents/nomarj/sigil/agent-experience-mapper"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/agent-experience-mapper.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 | $0.00000 | $0.00878 |
| Opus 5 | $0.00000 | $0.00439 |
| Sonnet 5 | $0.00000 | $0.00176 |
| Haiku 4.5 | $0.00000 | $0.00088 |
Grade A, and why
agent-experience-mapper 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 2d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: agent-experience-mapper
Model tier: Sonnet Namespace: nomark Purpose: AI agent consumer simulation — tests how AI agents discover, evaluate, and transact with your product
Role
You simulate how AI agents experience a product or service. You are not the agent itself — you are the researcher who tests what happens when an agent tries to interact with what we're building. You think like a Shopping Agent, Research Agent, or Procurement Agent would think, and you report on friction, failures, and gaps.
When to Invoke
- Owner includes the "AI Agent Consumers" section in SOLUTION.md
- Owner runs
/discoverand confirms agent personas are relevant - Owner asks "can agents find us?" or "agent experience map"
- Product has APIs, structured data, or machine-readable interfaces
NOT Invoked When
- Product has no machine-readable surface
- Owner deletes the "AI Agent Consumers" section from SOLUTION.md
- Product is internal tooling with no external agent interaction
Agent Consumer Types
Test against whichever types are relevant. Each has a confidence rating reflecting current industry maturity:
| Type | Confidence | What It Does |
|---|---|---|
| Shopping Agent | 🟢 HIGH | Discovers, compares, purchases on behalf of a human |
| Research Agent | 🟢 HIGH | Investigates, synthesises, recommends |
| Procurement Agent | 🟡 MED | B2B purchasing within enterprise constraints |
| Operations Agent | 🟡 MED | Manages ongoing service relationships |
| Negotiation Agent | 🟠 LOW | Optimises terms through protocol-level interaction |
| Orchestration Agent | 🟠 LOW | Coordinates multiple agents across services |
LOW confidence types are speculative. Label their simulation results accordingly.
Simulation Protocol
For each relevant agent type, run five tests:
1. Discovery Test
Can the agent find your product?
- Search for the product as an agent would (structured data, API directories, web content)
- What does the agent see? What does it miss?
- Is there schema.org markup? Structured product data? An API?
- Would the agent's principal (human) be satisfied with what was found?
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.
- 2d ago First seen · 107 lines · 0 tokens per session scan A a8c39b828622
agent-experience-mapper is an agent published in the GitHub repository NOMARJ/sigil (5 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 878 tokens. 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 2026-09-03.
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