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 gaasher/Agent-Loop-Skills --skill literature-surveygit clone --depth 1 https://github.com/gaasher/Agent-Loop-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/gaasher/agent-loop-skills/literature-survey)<a href="https://agentmods.dev/skills/gaasher/agent-loop-skills/literature-survey"><img src="https://agentmods.dev/badge/skills/gaasher/agent-loop-skills/literature-survey/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/gaasher/agent-loop-skills/literature-survey"><img src="https://agentmods.dev/badge/skills/gaasher/agent-loop-skills/literature-survey.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Agent Snooping · line 64 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00176 | $0.02417 |
| Opus 5 | $0.00088 | $0.01208 |
| Sonnet 5 | $0.00035 | $0.00483 |
| Haiku 4.5 | $0.00018 | $0.00242 |
Grade A, and why
literature-survey 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Survey Loop
A search → extract → map → expand loop that builds an evidence/contradiction matrix and stops
at saturation. The artifact is the matrix (claims × sources, with each source's stance); the
feedback signal is how many new, matrix-changing sources a round adds — you keep expanding until
that falls below <min_new> for <patience> rounds. Unlike a one-shot summary, the loop deliberately
hunts contradictions and gaps and keeps pulling threads until the picture stops changing.
The discipline: every cell — a source's stance on a claim — is backed by a verbatim snippet from a real retrieval. The value is not a tidy narrative; it is an honest map of where the literature agrees, disagrees, and is silent.
When to use
Use this for a multi-source survey of a question where the deliverable is a structured map of the evidence, not a paragraph. Default: run the full expand→admit→map loop below until saturation. Escape hatch: if the user wants only a quick scan, run round 0 (seed) alone and hand back the seed matrix. Not for grading a written proposal against the literature, and not for proposing new hypotheses.
Setup
Resolve bindings interactively. If loop.run.yaml exists in the working dir, load it, confirm the
values in one line, and skip to the loop. Otherwise: on Claude Code (the AskUserQuestion tool is
available) infer a likely value for each binding and present it as the recommended option; on other
hosts ask each as a quoted plain-text prompt. Then write loop.run.yaml (format:
examples/run.example.yaml) and confirm every value plus the live/degraded literature tier before
creating any other files.
| binding | meaning | default | how to infer |
|---|---|---|---|
<question> |
the survey question/topic, with any scope (years, sub-fields, inclusion criteria) | — | ask the user; restate the scope back for confirmation |
<eval_scale> |
depth per round (low/medium/high, see below) |
medium |
— |
<matrix> |
structured output matrix (validates schemas/matrix.schema.json); survey.md written alongside |
<sandbox_root>/matrix.json |
— |
<sandbox_root> |
where the matrix, survey.md, ledger, and lit cache live |
./sandbox |
— |
<budget> |
max rounds | 6 | — |
<patience> |
stop after this many consecutive "dry" rounds | 2 | — |
<min_new> |
saturation threshold — a round is "dry" if it adds fewer than this many new, matrix-changing sources | 2 | — |
What ships with it
2 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 · 149 lines · 176 tokens per session scan A 5f6db3970bce
literature-survey is a skill published in the GitHub repository gaasher/Agent-Loop-Skills (169 stars, last pushed 2mo ago), licensed MIT. It adds 176 tokens to every session and 2,417 once invoked, about $0.0009 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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