loader
Skill1 starsChanged 30 days agoMITView on GitHub
Instructions for the upstream workflow: Assemble the context a delegated sub-agent needs — the shared core agent file plus the agent's own delta — with single and batch loading and a helper that suggests which agents fit a task. Use when spawning named agents that must share one contract. Not for choosing among tools — use tool-router or skill-finder; not for loading skills into the context under a budget — use context-budget.
1 other project uses a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- zedarvates/botte-secreteedited, first seen Aug 8, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
- zedarvates/botte-secrete★ 290% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository114 other files it gives its agents.
- agent-cacheSkill
- agent-compressionSkill
- agent-intelSkill
- agent-overlapSkill
- agent-stateSkill
- ambient-hudSkill
- app-testSkill
- audit-dagSkill
- auto-distillSkill
- auto-memorySkill
- auto-routerSkill
- benchSkill
- bootstrapSkill
- botte-learnSkill
- botte-nnSkill
- botte-proxySkill
- botte-wrapSkill
- cacheSkill
- call-chainsSkill
- capabilitiesSkill
- cardinalSkill
- checkupSkill
- clarificationSkill
- clusterSkill
- code-complexitySkill
- code-duplicationSkill
- code-fingerprintSkill
- code-rulesSkill
- code-stateSkill
- code-wrappersSkill
- comfyuiSkill
- completion-proofSkill
- conductorSkill
- context-budgetSkill
- context-compressorSkill
- context-profilerSkill
- context-slicerSkill
- context-windowsSkill
- control-loopSkill
- cost-estimatorSkill
- dag-optimizerSkill
- dashboardSkill
- decision-ladderSkill
- demoSkill
- diff-languageSkill
- directives-auditSkill
- docgenSkill
- docs-stewardSkill
- dynamic-workflowsSkill
- efficiencySkill
- eventsSkill
- fallow-likeSkill
- fallowSkill
- fast-contextSkill
- fixSkill
- fleetSkill
- hailo-visionSkill
- harness-deltaSkill
- harvestSkill
- hermes-bridgeSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 22
Trigger: When using delegate_task to spawn Mousquetaires or Cardinal agents.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Pre-Prompt Loader
Package scope and prerequisites
This catalog ships instructions, not the executable runtime. Python modules, scripts, local services and optional tools named below must be installed separately from the upstream project. Check their availability before running commands; if they are missing, explain the prerequisite instead of claiming execution or results. The host agent may use model tokens while following these instructions.
When NOT to use
- You need a tool selected, not an agent's context assembled — use tool_router.
- You need a subset of skills loaded under a budget — use context_budget. Loads core-agent.md + agent delta for delegate_task subagents.
Trigger: When using delegate_task to spawn Mousquetaires or Cardinal agents.
Usage:
from skills.loader import load_agent, load_agents_batch, suggest_agents
ctx = load_agent("porthos", project_root="/path/to/project")
tasks = load_agents_batch([("porthos","Audit",None), ("aramis","Optimize",None)])
suggestions = suggest_agents("reassess inherited architecture assumptions")Module: skills/loader
Agents: 9 (porthos, dartagnan, aramis, athos, rochefort, milady, comte_de_wardes, cardinal, monte_cristo)
monte_cristo is neither blue nor red. It uses the canonical read-only agent
definition in agents/monte-cristo.md and receives no terminal toolset.
suggest_agents(goal) performs deterministic, zero-token special-agent routing.
It fails closed unless Monte-Cristo's tracked trigger-evaluation gate passes.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

