Lychee is a self-hosted web application for uploading, organizing, managing, and sharing photographs. It is for people who want to run their own photo gallery and management system on a server or web space.
Borrowing it
Nothing to install: this file belongs to LycheeOrg/Lychee. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/LycheeOrg/Lychee/master/AGENTS.mdgit clone --depth 1 https://github.com/LycheeOrg/LycheeWrote 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/instructions/lycheeorg/lychee/agents-md)<a href="https://agentmods.dev/instructions/lycheeorg/lychee/agents-md"><img src="https://agentmods.dev/badge/instructions/lycheeorg/lychee/agents-md/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/instructions/lycheeorg/lychee/agents-md"><img src="https://agentmods.dev/badge/instructions/lycheeorg/lychee/agents-md.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 | $0.04193 | $0.04193 |
| Opus 5.5 | $0.01677 | $0.01677 |
| Sonnet 5.5 | $0.00839 | $0.00839 |
| Haiku 4.5 | $0.00419 | $0.00419 |
Grade C, and why
Lychee AGENTS.md 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 21d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- **No surprises.** Avoid destructive commands (e.g., `rm -rf`, `git reset --hard`) unless the user requests them. Stay within the repository sandbox. How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before You Code
- Clarify ambiguity first. Do not plan or implement until every requirement is understood. Ask the user, record unresolved items in the feature's own
docs/specs/4-architecture/features/<NNN>-<feature-name>/open-questions.md(create it from docs/specs/templates/feature-open-questions-template.md if missing), and wait for answers. Capture accepted answers by updating the relevant specification’s requirements/NFR/behaviour/telemetry sections so the spec remains the single source of truth for behaviour.- No-direct-question rule: For feature work, never ask the user for clarification, approval, or a decision in chat until the matching open question is logged in the feature's
open-questions.md(table row + Question Details entry). Treat violations as blockers—stop work, add the missing entry, then resume the conversation by referencing that question ID. - Governance/tooling exemption: Questions about work that belongs to no feature (AGENTS.md, runbooks, templates, conventions, scripts, CI) are asked directly in chat without logging. Still present them in the Options A, B, C format below, ordered by preference, and record the outcome in the governing document itself.
- Whenever you present alternative approaches—whether for open questions or general solution proposals—first capture or update the entry in the feature's
open-questions.md(summary row + Question Details section) so the ambiguity lives on disk, then present the stored text to the user inline in chat. Summarise the options directly in your reply (do not tell the user to open the file), call out the question ID (for example, Q-013-01), and follow the numbered-heading/Options A, B, C format with pros/cons. Order the options by preference (Option A is always the recommended path, Option B the next-best, etc.) so the user sees our best advice first. Keep specifications/plans/tasks limited to that ID until the question is resolved.
- No-direct-question rule: For feature work, never ask the user for clarification, approval, or a decision in chat until the matching open question is logged in the feature's
- Work in small steps. During planning, break every change into logical, self-contained tasks that are expected to complete within ≤90 minutes. Execution can take longer if required; the goal is to plan manageable increments, and prepare a Conventional Commit for each finished slice (see Commit protocol).
- Prime the knowledge map. Skim docs/specs/4-architecture/knowledge-map.md and the up-to-date module snapshot in docs/specs/architecture-graph.json before planning so new work reinforces the architectural relationships already captured there.
- Template usage. Author new specifications, feature plans, task checklists, and open-questions logs using docs/specs/templates/feature-spec-template.md, docs/specs/templates/feature-plan-template.md, docs/specs/templates/feature-tasks-template.md, and docs/specs/templates/feature-open-questions-template.md so structure, metadata, and verification notes stay uniform across features.
- ADR context. Before planning or implementation, skim ADRs under
docs/specs/6-decisions/whose related-features/specs entries reference the active feature ID so high-impact clarifications and architectural decisions are treated as required context alongside the roadmap, spec, plan, tasks, and knowledge map.
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.
- 21d ago Changed · +14 tokens per session eb61be1ea651
- 1mo ago Changed · +422 tokens per session d755b14b5de5
- 2mo ago First seen · 123 lines · 3,757 tokens per session scan C 12d64f7df591
Lychee AGENTS.md is an instructions file published in the GitHub repository LycheeOrg/Lychee (4,330 stars, last pushed yesterday), licensed MIT. It adds 4,193 tokens to every session, about $0.0168 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Lychee AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| Lychee AGENTS.mdLycheeOrg/Lychee | Instructions file | 4.3k | yesterday | MIT | C | 4,193 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |