Borrowing it
Nothing to install: this file belongs to zkysar1/Claude-Mind. 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/zkysar1/Claude-Mind/main/.claude/skills/aspirations-learning-gate/SKILL.mdgit clone --depth 1 https://github.com/zkysar1/Claude-MindWrote 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/zkysar1/claude-mind/aspirations-learning-gate)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/aspirations-learning-gate"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/aspirations-learning-gate/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/zkysar1/claude-mind/aspirations-learning-gate"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/aspirations-learning-gate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00088 | $0.05684 |
| Opus 5 | $0.00044 | $0.02842 |
| Sonnet 5 | $0.00018 | $0.01137 |
| Haiku 4.5 | $0.00009 | $0.00568 |
Grade A, and why
aspirations-learning-gate 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 10d 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 — 439 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aspirations-learning-gate — Obligation Enforcement Gates
CRITICAL: This is the obligation enforcement sub-skill. It prevents the loop from continuing without learning. If this sub-skill is skipped, knowledge debt accumulates and the agent drifts into "busy but not learning" mode.
Abbreviation Policy
Mandatory writes for this obligation: see core/config/obligation-schema.yaml
→ obligations.learn. Abbreviation is permitted only when
context_budget.zone == tight. The zone is distance-to-autocompact, not raw
usage — see core/scripts/context-budget-status.py classify_zone for the
source of truth. Before abbreviating, Bash: bash core/scripts/context-budget-banner.sh and quote its output; the banner line
is the evidence that makes the "tight" claim verifiable. When abbreviating,
log TWO lines in the journal entry (in this order):
OBLIGATION ABBREVIATED: learn — {condition}
CTX: raw N% | of-autocompact N% | zone tight | headroom N tokens | env ... | updated ...
The banner line must be the actual output captured from the banner script in
this iteration. core/scripts/context-citation-audit.sh scans for the pair
and reports any tight-zone claim that lacks its banner line. Then satisfy
minimum_inline (sensory-buffer append OR reasoning-bank-add, then
wm-set loop_state). Otherwise invoke this Skill literally. Phase 9.5d
(below) audits the PREVIOUS iteration's abbreviation claims against the
context-budget state captured at that time; false claims accumulate in
agents/<agent>/session/obligation-audit.jsonl and 3+ in a session auto-file a
single Investigate: false-abbreviation-claims goal.
Step 0: Load Conventions — Bash: load-conventions.sh with each name from the conventions: front matter.
Inputs (from orchestrator)
goal: The executed goaloutcome_class: "routine" or "deep"goals_completed_this_session: Running counter (all goals)productive_goals_this_session: Running counter (productive outcomes only)batch_mode: Boolean (was this a batched execution?)prefetch_goals: Any pre-fetched research resultsgoals_since_last_tree_update: From session_signals — encoding drift counter
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.
- 10d ago First seen · 439 lines · 88 tokens per session scan A 52d3ddf94701
aspirations-learning-gate is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed 2d ago), licensed MIT. It adds 88 tokens to every session and 5,684 once invoked, about $0.0004 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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