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 commands/fmarzochi/egc/projectsgit clone --depth 1 https://github.com/Fmarzochi/EGCWrote 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/commands/fmarzochi/egc/projects)<a href="https://agentmods.dev/commands/fmarzochi/egc/projects"><img src="https://agentmods.dev/badge/commands/fmarzochi/egc/projects.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00006 | $0.00110 |
| Opus 5 | $0.00003 | $0.00055 |
| Sonnet 5 | $0.00001 | $0.00022 |
| Haiku 4.5 | $0.00001 | $0.00011 |
Grade A, and why
projects 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 today.
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.
What it actually says
Projects Command
Show continuous-learning-v2 project registry and stats: $ARGUMENTS
Your Task
Run:
python3 "${GEMINI_PLUGIN_ROOT}/skills/continuous-learning-v2/scripts/instinct-cli.py" projects
If GEMINI_PLUGIN_ROOT is unavailable, use:
python3 ~/.gemini/skills/continuous-learning-v2/scripts/instinct-cli.py projects
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.
- today First seen · 24 lines · 6 tokens per session scan A 038ced1de58e
projects is a command published in the GitHub repository Fmarzochi/EGC (48 stars, last pushed today), licensed Apache-2.0. It adds 6 tokens to every session and 110 once invoked, about $0.0000 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 2026-09-03.
Other commands, from other repositories
demand-discovery
Run automated niche demand discovery research across 7 data sources and 26 categories.
tdd-workflow
Implement the behavior described in $ARGUMENTS using strict TDD. Follow this exact sequence. Do not collapse phases. Each gate requires actual test runner output.
api-add-endpoint
Create a new API endpoint. $ARGUMENTS should describe the endpoint (e.g., "POST /api/users - create a user").
code-review
Review the code changes in this project. For each file changed.
refactor-file
Refactor the file specified in $ARGUMENTS following project conventions.
api-test-endpoint
Test the API endpoint specified in $ARGUMENTS.