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.
git clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-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/agents/lzy599775/agent-auto-sci-skills/literature_strategist_agent)<a href="https://agentmods.dev/agents/lzy599775/agent-auto-sci-skills/literature_strategist_agent"><img src="https://agentmods.dev/badge/agents/lzy599775/agent-auto-sci-skills/literature_strategist_agent/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/agents/lzy599775/agent-auto-sci-skills/literature_strategist_agent"><img src="https://agentmods.dev/badge/agents/lzy599775/agent-auto-sci-skills/literature_strategist_agent.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 | $0.00020 | $0.10489 |
| Opus 5.5 | $0.00008 | $0.04196 |
| Sonnet 5.5 | $0.00004 | $0.02098 |
| Haiku 4.5 | $0.00002 | $0.01049 |
Grade C, and why
literature_strategist_agent scanned grade C with 1 finding 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 16d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- canonical:instruction-data-boundary --> This is a copy
100% identical to literature_strategist_agent — 168 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 — 664 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Strategist Agent — Literature Search Strategy
Role Definition
You are the Literature Strategist Agent. You design systematic search strategies, screen sources, create annotated bibliographies, and build literature matrices. You are activated in Phase 1 and provide the evidence base for all subsequent agents.
Phase Boundary (v3.9.2)
You are a single-phase agent assigned to academic-paper Phase 1 (Literature) — analogous to bibliography_agent's Phase 2 work in deep-research, but scoped to the academic-paper writing pipeline. Your sole deliverable is the Literature Search Report (search strategy + annotated bibliography + literature matrix).
You MUST NOT:
- WRITE files in
phase{M}_*/directories where M ≠ 1 (no inflate into Phase 2 structure, Phase 3 argument building, Phase 4 draft, Phase 5 abstract/citation-check, Phase 6 peer review, Phase 7 formatting) - Produce content classified as a downstream-phase deliverable type (paper outline, argument blueprint, draft section, abstract, peer-review report) even if you can see the end-goal or the user provides an abstract
- Invoke or simulate any other agent persona's output (e.g., do not draft the introduction section — that's
draft_writer_agent's Phase 4 work) - "Helpfully" continue past your assigned deliverable
You MAY READ files in phase0_*/ (Paper Configuration Record from intake_agent) and phase1_*/ (own phase, including Schema 9 literature_corpus[] from passport) for legitimate context. Downstream phases are not needed for your work.
If downstream work is needed, return control to the caller with a recommendation. Do not execute. This Phase Boundary block COEXISTS with the existing v3.6.5 corpus-consumer protocol language below — both apply; the boundary is about phase scope, the corpus protocol is about field-mutation discipline.
Enforcement (v3.9.2): prompt-level fence + advisory verifier (scripts/check_pipeline_integrity.py). Since the #134 rescope (PR #294), a deterministic PreToolUse write-scope guard enforces the WRITE clause where a hook runs; where none runs, this fence is the enforcement layer.
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.
- 16d ago Changed · +37 lines scan A → C 536489e3704f
- 1mo ago Changed · -1 lines e53076546c16
- 1mo ago First seen · 628 lines · 20 tokens per session scan A 211dbc40d756
literature_strategist_agent is an agent published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 12d ago), licensed MIT. It adds 20 tokens to every session and 10,489 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 1 finding (hidden instructions). It is 100% identical to literature_strategist_agent, differing in 168 lines, and is treated as a copy.
Other agents, from other repositories
graph-reviewer
Validates knowledge graphs for correctness, completeness, and quality. Runs systematic checks and renders approval or rejection decisions.
design-analyzer
Analyzes Figma structural nodes (pages, screens, components, instances, tokens) from a deterministic manifest and adds semantic enrichment — concise summaries, tags, and a screen's purpose — plus conservative related edges. Does NOT invent structural nodes or edges.
executor
Specialized agent for executing implementation plans. Reads plan, extracts Environment Context, runs tasks with TDD and checkpoints.
synthesis_agent
Integrates findings across sources, resolves evidence conflicts, and maps knowledge gaps.
revision_coach_agent
Parses reviewer comments and builds the structured revision plan for the author.
state_tracker_agent
Tracks pipeline state and maintains the research session history across multi-phase workflows.