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 agentmods add skills/markmhendrickson/ateles/learnnpx skills add markmhendrickson/ateles --skill learngit clone --depth 1 https://github.com/markmhendrickson/atelesWhat 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 | $0.00025 | $0.01523 |
| Opus 5 | $0.00013 | $0.00762 |
| Sonnet 5 | $0.00005 | $0.00305 |
| Haiku 4.5 | $0.00003 | $0.00152 |
Grade A, and why
learn 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 2d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn
Turn a behavior miss raised in chat into a permanent process improvement.
Use this skill when the user points out an omission, asks why something was not done, or requests stronger automatic agentic behavior.
Goals
- Fix the immediate omission in the current turn.
- Prevent recurrence by updating the smallest durable artifact (rule, skill, or hook).
- Apply the new guidance immediately in the given chat context—perform the newly required behavior in this conversation, not only document it.
Inputs
issue_statement(required): What behavior was missed.scope_hint(optional):repo,local_mcp, or specific path.target_behavior(optional): Desired default behavior going forward.
Workflow
-
Capture the failure clearly
- Restate: expected behavior, actual behavior, and impact.
- Confirm whether the missed action was not explicitly requested earlier in the turn flow (retrospective improvement case).
-
Select the right remediation artifact
- Rule update when behavior should be globally or repeatedly enforced.
- Skill update/new skill when behavior is a multi-step workflow.
- Hook/script update when behavior must be automatically enforced by tooling (for example, pre-commit checks or setup hooks).
- MCP source-repo instruction update when omission is due to MCP instruction quality or ordering.
-
Choose the repository to change
- Current repo (
ateles) for local agent workflow defaults, repo rules, and repo skills. - Relevant local MCP source repo when the issue is MCP-instruction behavior (for example Neotoma instruction text in sibling repo).
- Priority rule: If the miss concerns Neotoma interactions, default to improving Neotoma's own instruction source first; use
atelesonly for non-MCP workflow behavior. - Prefer the smallest repository scope that fixes the issue for future runs.
- Never add or modify ateles rules (or skills/hooks) to compensate for behavior that should be enforced by MCP server instructions. If the root cause is MCP instruction quality or ordering, fix the MCP source repo only; do not duplicate or compensate in this repo.
- Current repo (
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.
- 2d ago First seen · 102 lines · 25 tokens per session scan A 3f16e605a860
learn is a skill published in the GitHub repository markmhendrickson/ateles (5 stars, last pushed 5d ago), licensed MIT. It adds 25 tokens to every session and 1,523 once invoked, about $0.0001 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 2026-08-31.
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arbor-agent-plugins-hitl-budget
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bernstein-run
Run a verified multi-agent goal with Bernstein. Use when a task is too large for a single agent session: Bernstein decomposes the goal into tasks, spawns CLI coding agents in parallel git worktrees, verifies their output, and merges results. Also use to check run status, costs, and to verify a finished run against its…
dynamic-tools
Runtime tool management with toolmanage and tools.toml format. Create, enable, disable, reload tools without restart. (/dynamic-tools, toolmanage, runtime tools).
bernstein-alerts
Show active alerts from Bernstein - failed tasks, stalled agents, budget warnings, blocked tasks needing human intervention. Use when the user asks about problems, errors, warnings, or what needs attention.