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/sairam0424/mindforge/mindforge-debugnpx skills add sairam0424/MindForge --skill mindforge-debuggit clone --depth 1 https://github.com/sairam0424/MindForgeWhat 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 | $0.00013 | $0.00948 |
| Opus 5 | $0.00006 | $0.00474 |
| Sonnet 5 | $0.00003 | $0.00190 |
| Haiku 4.5 | $0.00001 | $0.00095 |
Grade A, and why
mindforge-debug scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to thrunt-debug — 27 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrator role: Gather symptoms, spawn mindforge-debugger agent, handle checkpoints, spawn continuations.
Why subagent: Investigation burns context fast (reading files, forming hypotheses, testing). Fresh 200k context per investigation. Main context stays lean for user interaction.
Check for active sessions:
ls .planning/debug/*.md 2>/dev/null | grep -v resolved | head -5
0. Initialize Context
INIT=$(node ".agent/bin/mindforge-tools.cjs" state load)
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fi
Extract commit_docs from init JSON. Resolve debugger model:
debugger_model=$(node ".agent/bin/mindforge-tools.cjs" resolve-model mindforge-debugger --raw)
1. Check Active Sessions
If active sessions exist AND no $ARGUMENTS:
- List sessions with status, hypothesis, next action
- User picks number to resume OR describes new issue
If $ARGUMENTS provided OR user describes new issue:
- Continue to symptom gathering
2. Gather Symptoms (if new issue)
Use AskUserQuestion for each:
- Expected behavior - What should happen?
- Actual behavior - What happens instead?
- Error messages - Any errors? (paste or describe)
- Timeline - When did this start? Ever worked?
- Reproduction - How do you trigger it?
After all gathered, confirm ready to investigate.
3. Spawn mindforge-debugger Agent
Fill prompt and spawn:
<objective>
Investigate issue: {slug}
**Summary:** {trigger}
</objective>
<symptoms>
expected: {expected}
actual: {actual}
errors: {errors}
reproduction: {reproduction}
timeline: {timeline}
</symptoms>
<mode>
symptoms_prefilled: true
goal: find_and_fix
</mode>
<debug_file>
Create: .planning/debug/{slug}.md
</debug_file>
Task(
prompt=filled_prompt,
subagent_type="mindforge-debugger",
model="{debugger_model}",
description="Debug {slug}"
)
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 First seen · 164 lines · 13 tokens per session scan A 962a0600a736
mindforge-debug is a skill published in the GitHub repository sairam0424/MindForge (0 stars, last pushed 2d ago), licensed MIT. It adds 13 tokens to every session and 948 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to thrunt-debug, differing in 27 lines, and is treated as a copy.
Other skills, from other repositories
ciel-antigravity-lookup
Find Antigravity conversations on macOS by UUID or keyword.
workspace-mirror
Sync and backup Antigravity IDE sessions, transcripts, SQLite database metadata, and brain artifacts locally into a structured workspace directory (.gemini-local/) with a rich interactive viewer.html page. Use this skill whenever the user mentions backups, workspace syncing, fswatch real-time mirroring, viewing…
agent-harness-fault-injection
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
aria
Designs the data model, API contracts, and structural foundation of the system.
peon-ping-log
Log exercise reps for the Peon Trainer. Use when user says they did pushups, squats, or wants to log reps. Examples - "/peon-ping-log 25 pushups", "/peon-ping-log 30 squats", "log 50 pushups".
agy-delegate
Delegate a coding task to the Google Antigravity CLI (agy) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Antigravity or agy - phrasings like "have Antigravity do X", "delegate this to agy", "run it through agy", or "use…