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 skills add tonone-ai/tonone --skill apex-recongit clone --depth 1 https://github.com/tonone-ai/tononeWrote 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/tonone-ai/tonone/apex-recon)<a href="https://agentmods.dev/skills/tonone-ai/tonone/apex-recon"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/apex-recon/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/tonone-ai/tonone/apex-recon"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/apex-recon.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00058 | $0.00803 |
| Opus 5.5 | $0.00023 | $0.00321 |
| Sonnet 5.5 | $0.00012 | $0.00161 |
| Haiku 4.5 | $0.00006 | $0.00080 |
Grade A, and why
apex-recon 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 23d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineering Reconnaissance
You are Apex — the engineering lead on the Engineering Team. Map the project before you plan anything.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
Steps
Step 0: Detect Environment
Scan the workspace for project structure indicators:
ls -la
cat CLAUDE.md 2>/dev/null || cat README.md 2>/dev/null | head -40
git remote -v 2>/dev/null
Step 1: Inventory Project Structure
Identify and document:
- Tech stack — languages, frameworks, build tools (read package.json, pyproject.toml, go.mod, Cargo.toml, etc.)
- Project layout — key directories and their purpose
- Entry points — main service files, API routers, CLI entry points
- Configuration — environment files, feature flags, config schemas
Step 2: Inventory Active Work
git log --oneline -20
git branch -a
git status
Document:
- Recent commits — what changed in the last 20 commits, by whom
- Open branches — what work is in flight
- Uncommitted changes — anything staged or unstaged
- Open TODOs — scan for TODO/FIXME/HACK comments in source
Step 3: Assess Technical Health
Evaluate at a glance:
- Test coverage signal — are there tests? CI config? Last test run outcome?
- CI/CD state — deployment pipeline present? Last deploy date?
- Dependency health — any obvious outdated or vulnerable deps?
- Documentation — is there a CLAUDE.md, docs/, or ADR directory?
- Specialist plugins — which tonone agents are installed (
.claude-plugin/)?
Step 4: Present Assessment
## Engineering Reconnaissance
**Stack:** [primary language + framework] | **Runtime:** [version]
**Repo:** [name] | **Branch:** [current] | **Last commit:** [date + message]
### Project Structure
[key dirs and their purpose — 5-8 lines max]
### Active Work
- **In-flight branches:** [N] — [list names]
- **Recent focus:** [summary of last 20 commits in 1-2 sentences]
- **Uncommitted changes:** [none / N files]
### Health Signals
- [GREEN/YELLOW/RED] Tests: [present and recent / stale / absent]
- [GREEN/YELLOW/RED] CI/CD: [configured / partial / absent]
- [GREEN/YELLOW/RED] Docs: [CLAUDE.md + docs / partial / none]
### Recommended Starting Point
[1-2 sentence recommendation on where to focus before planning]
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.
- 23d ago First seen · 94 lines · 58 tokens per session scan A fb0f1095a93b
apex-recon is a skill published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 9d ago), licensed MIT. It adds 58 tokens to every session and 803 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-20.
Other skills, from other repositories
fleet
The session roster (/foundry:fleet) — native /list-agents annotated with each row's foundry programme, over the NATIVE session/container list. Read-only/advisory. Trigger to see all your parallel sessions and containers at a glance with their foundry context, or when supervising many sessions and asking "what is each…
g-init
The single G-Forge front door — run once after installing the plugin. Detects what's here and routes to /g-onboard (existing codebase) or /g-kickoff (new project) for the brief, scaffolds CLAUDE.md (compact G-rules), g-docs/ROADMAP.md (with the Active Session handoff), g-docs/milestones/, g-docs/todo.md, the…
g-onboard
Onboard G-Forge onto an existing codebase. Reads deeply before asking anything — treats existing CLAUDE.md, rules, agents, and task ledgers as first-class inputs. Only interviews for what it genuinely doesn't know yet. Produces or updates g-docs/projectbrief.md.
g-roadmap
Project-manager-driven milestone planner. Gated phases — feature dump → cluster → sequence → premortem & re-prioritize → approve → write. Narrates reasoning at every step, and runs a premortem + re-prioritization of the whole roadmap whenever a milestone is added or modified. Auto-triggers when no g-docs/ROADMAP.md…
g-roundtable
Bind the session to "the Roundtable" — a shared live Doc that is the human-facing communication layer between you, non-programmers (PMs, collaborators), and the session. start binds a Doc (create-from-template or attach-by-URL); sync reads the Roundtable at a boundary and writes only salient deltas; close distills the…
g-telemetry
Compute the 8 reliability metrics defined in g-docs/telemetry-metrics.md, derive a health profile (stable / cautious / defensive / recovery), and write it to .claude/telemetry-profile for adaptive orchestration in /g-execute and /g-review. Read-only on history; never modifies retros, forecasts, or git state.