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-consolidate/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-consolidate)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/aspirations-consolidate"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/aspirations-consolidate/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-consolidate"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/aspirations-consolidate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Rogue Agent · line 1020 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00106 | $0.19488 |
| Opus 5 | $0.00053 | $0.09744 |
| Sonnet 5 | $0.00021 | $0.03898 |
| Haiku 4.5 | $0.00011 | $0.01949 |
Grade A, and why
aspirations-consolidate 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 3d 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 — 1,267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session-End Consolidation Pass
Run when the aspirations loop stops (any stop condition). This is the hippocampal "sleep replay" that compresses session observations into long-term memory. Covers micro-hypothesis sweep, encoding queue processing, dynamic consolidation budget, overflow queue management, encoding competition, tree encoding, knowledge debt sweep, snapshot invalidation, experience archive maintenance, journal logging, working memory archival, tree rebalancing, skill health report, aspiration archive sweep, user goal recap, continuation handoff, and restart loop cycle.
Note: Consolidation MUST NOT call session-state-set.sh. Only /start and /stop may change agent-state.
Note: minimum_mode is autonomous but /stop's deferred sequence (Phase -1.4 in aspirations/SKILL.md)
invokes this AFTER setting state to IDLE (D1) and BEFORE setting mode to reader (D7).
The mode is still autonomous at invocation time (D4). If Phase -1.4 step ordering changes, this breaks.
Parameters
-
stop_mode(boolean, default: false) — When true, skip Steps 7 (skill gap review), 7.5 (experience-to-skill mining), 8 (skill health report), 8.7 (user goal recap), and 10 (restart). Used by /stop to run proper consolidation without restarting the loop. -
goals_completed_this_session(int) — close-EVENT count for the session, passed by/aspirations(SKILL.md L727/L735). The orchestrator derives it fromloop_state.goals_completed, NOT from working memory. -
session_count(int),evolutions_this_session(int) — passed in the same two calls.These three were passed by the caller but UNDECLARED here until g-115-4935, and that gap is the root cause of the defect it fixes. Undeclared, Step 8.87 reached for a working-memory field that merely SHARES THE NAME
goals_completed_this_session— a top-level WM key (wm.py TOP_LEVEL_KEYS) holding a LIST, not this int. That read also lands AFTER Step 5's wm-reset, which returns the list to its[]template value because the only top-level field surviving reset is SESSION_IDENTITY_FIELDS = {"session_start"}. So the team-state field published a stale prior-session figure: measured 2026-08-04 (alpha, cc-04) at 125 where the true count was 270 — and 270 is exactly whatloop_state.goals_completed, i.e. this parameter, already held.
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.
- 3d ago Changed 00c9e6efaef1
- 11d ago First seen · 1,267 lines · 106 tokens per session scan A 4f88b451c792
aspirations-consolidate is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed 3d ago), licensed MIT. It adds 106 tokens to every session and 19,488 once invoked, about $0.0005 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.
Other skills, from other repositories
hive.context-preservation
Proactively extract critical values from tool results into working notes before automatic context pruning destroys them.
hive.note-taking
Maintain a free-form scratchpad of decisions, extracted values, and open questions so context pruning doesn't lose anything you still need.
Vizra ADK Memory System
Implement persistent memory, session context, and vector memory (RAG) for AI agents.
learning-capture
Log corrections, errors, and discoveries to orbital/LESSONS.md so future sessions avoid repeating mistakes.
obsidian
A skill for working with an Obsidian vault, which is a folder of Markdown notes used as a personal knowledge base. It covers creating, extending, searching, and organizing notes, including links, tags, folders, and daily entries.
mupeng-sync
Propagate Mupengism values and knowledge to new agents. Deploy AGENT-VALUES.md, onboard new subagents with core principles. The missionary skill.