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-execute/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-execute)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/aspirations-execute"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/aspirations-execute/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-execute"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/aspirations-execute.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 205 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00119 | $0.18956 |
| Opus 5 | $0.00060 | $0.09478 |
| Sonnet 5 | $0.00024 | $0.03791 |
| Haiku 4.5 | $0.00012 | $0.01896 |
Grade A, and why
aspirations-execute 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 yesterday.
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 — 1,384 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phase 4: Goal Execution
Invoked as Phase 4 of the aspirations loop after goal selection (Phase 2) and decomposition (Phase 3). Covers the full execution pipeline: precondition checking, intelligent LLM-driven retrieval, memory deliberation, agent delegation, primary execution, fail-fast cascade, experience archival, context utilization feedback, domain post-execution steps, knowledge reconciliation, and batch execution.
Inputs (from orchestrator)
goal: Selected goal object from Phase 2aspiration_id: Parent aspiration IDsource: Queue origin ("world"or"agent") — pass--source {source}to allaspirations-*.shcallsbatch_mode: Boolean (from Phase 2)outcome_class: Set by Phase 4-post after execution
Step 0: Load Conventions — Bash: load-conventions.sh with each name from the conventions: front matter. Read only the paths returned (files not yet in context). If output is empty, all conventions already loaded — proceed to next step.
Execution Autonomy Rule
The agent makes ALL decisions autonomously during goal execution — never stops to ask "should I push?" or "what next?". Phase 4.2 domain steps handle push/deploy; the loop handles selection.
For significant judgment calls (architecture choices, deploy strategy,
trade-offs), pick the safer/simpler option when unsure, then log one
pq-NNN entry in agents/<agent>/session/pending-questions.yaml framing it as
"I decided {X} because {Y} — override if you disagree" with
default_action: "Already executed: {what}" + status: pending. User
reviews retroactively via /respond or session recap. Continue immediately.
Cognitive Primitives (Always Available)
During ANY phase — goal execution, error handling, reflection, spark checks —
the agent can create goals from things it notices. Five types: Unblock
(CREATE_BLOCKER only — see its digest), Investigate, Idea,
Maintain (inline framework fix, status: completed on creation),
Cross-Agent Insight (posted to findings board).
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.
- yesterday Changed fa2967b5a701
- 9d ago First seen · 1,384 lines · 119 tokens per session scan A 0a0bf1919c1c
aspirations-execute is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed yesterday), licensed MIT. It adds 119 tokens to every session and 18,956 once invoked, about $0.0006 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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