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 gohypergiant/agent-skills --skill epistemic-mappergit clone --depth 1 https://github.com/gohypergiant/agent-skillsWrote 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/gohypergiant/agent-skills/epistemic-mapper)<a href="https://agentmods.dev/skills/gohypergiant/agent-skills/epistemic-mapper"><img src="https://agentmods.dev/badge/skills/gohypergiant/agent-skills/epistemic-mapper/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/gohypergiant/agent-skills/epistemic-mapper"><img src="https://agentmods.dev/badge/skills/gohypergiant/agent-skills/epistemic-mapper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 360 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- medium Prompt Injection · line 3 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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 | $0.00200 | $0.05353 |
| Opus 5 | $0.00100 | $0.02677 |
| Sonnet 5 | $0.00040 | $0.01071 |
| Haiku 4.5 | $0.00020 | $0.00535 |
Grade A, and why
epistemic-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 11d 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 — 412 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Epistemic Mapper
Extract a project's knowledge state from its documentation and its code, then
sort every observation into one of four quadrants and write the result into
a canonical EPISTEMIC-MAP.md. This is a handoff artifact: it exists because
a prototype builder holds a mass of tacit knowledge that never got written
down, and once a contract is signed and a team takes over, that knowledge
either gets captured now or gets rediscovered the hard way, in production.
HIGH CERTAINTY (validated)
|
[ ASSUMPTIONS ] | [ FACTS ]
Unknown Known | Known Known
nobody wrote it | proven, cited
down, but the | evidence
code/docs rely |
on it |
------------------------ + ------------------------
|
[ RISKS ] | [ QUESTIONS ]
Unknown Unknown | Known Unknown
blind spots, found | explicit open
only by looking | gaps, already
across everything | flagged somewhere
|
LOW CERTAINTY (unvalidated)
Relationship to Other Living Documents
CONSTRAINTS.md holds externally-imposed hard limits. JARGON.md holds term
definitions. ARCHITECTURE.md holds structural decisions. AGENTS.md holds
agent behavior and orchestration. EPISTEMIC-MAP.md is different in kind
from all four: it isn't a ledger of what's true, it's a map of how sure we
are about what's true. Read the other living docs (if present) before
extraction starts, for two reasons:
- Don't duplicate. If a Known Known is already stated in
CONSTRAINTS.mdor defined inJARGON.md, reference it by file and section instead of restating it as a new Fact.EPISTEMIC-MAP.mdshould point at the other living docs, not compete with them. - Seed confidence. A claim backed by an entry in
CONSTRAINTS.mdis about as validated as a claim gets — treat it as a Known Known withCONFIRMEDconfidence by default, not something to re-litigate.
What ships with it
7 files 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.
- 11d ago First seen · 412 lines · 200 tokens per session scan A 257e82ec0cfd
epistemic-mapper is a skill published in the GitHub repository gohypergiant/agent-skills (24 stars, last pushed yesterday), licensed Apache-2.0. It adds 200 tokens to every session and 5,353 once invoked, about $0.0010 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 2026-08-30.
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