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 nexus-substrate/nexus-agents --skill dogfooding-issuesgit clone --depth 1 https://github.com/nexus-substrate/nexus-agentsWrote 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/nexus-substrate/nexus-agents/dogfooding-issues)<a href="https://agentmods.dev/skills/nexus-substrate/nexus-agents/dogfooding-issues"><img src="https://agentmods.dev/badge/skills/nexus-substrate/nexus-agents/dogfooding-issues/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/nexus-substrate/nexus-agents/dogfooding-issues"><img src="https://agentmods.dev/badge/skills/nexus-substrate/nexus-agents/dogfooding-issues.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 Prompt Injection · line 72 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00073 | $0.00816 |
| Opus 5 | $0.00036 | $0.00408 |
| Sonnet 5 | $0.00015 | $0.00163 |
| Haiku 4.5 | $0.00007 | $0.00082 |
Grade A, and why
dogfooding-issues 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 11d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dogfooding Issues Skill
Process open issues following the self-development protocol.
Full workflows:
Pre-Flight Checks
TZ='America/New_York' date '+%Y-%m-%d %H:%M:%S %Z'
git status --short
gh issue list --state open --limit 20
Issue Selection
Check Research Registry First
grep -A 5 "status: planned" docs/research/registry/techniques.yaml | \
grep -B 5 "priority: P[12]"
Priority order:
- P1 techniques with existing issues
- P2 techniques with clear implementation path
- Bug fixes blocking other work
- Documentation gaps
Implementation
Follow CONTRIBUTION_GUIDE.md:
- Research - Check registry, verify dependencies
- Interface First - Define before implementation
- TDD - Write failing test, implement, refactor
- Registry Update - Change
status: planned→status: implemented - Commit - Reference issue, update registry
Quality Checklist
See CODING_STANDARDS.md:
- Tests pass, lint/types clean
- Coverage ≥ 80%
- Registry updated (if technique)
- Issue referenced in commit
Anti-rationalization — Dogfooding
| Excuse | Counter |
|---|---|
| "Pick the easy issue first" | Easy + un-implemented is suspicious — usually means the issue isn't actually easy or the spec is wrong. Pick by impact, not by ease. |
| "Skip the research check" | The research registry is where prior thought lives. Skipping it means re-deriving solutions and missing prior decisions. |
| "Test coverage 80% is fine" | Per CLAUDE.md, the gate is 89.66% / 93.26% (statement / function). Don't ship below the existing floor. |
| "Implementation is partial — flag mark as 'in progress'" | Per implement-feature: don't mark implemented if partial. Either ship the slice or split the issue. |
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.
- 11d ago First seen · 93 lines · 73 tokens per session scan A fedb6fbd58ca
dogfooding-issues is a skill published in the GitHub repository nexus-substrate/nexus-agents (18 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 816 once invoked, about $0.0004 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 2026-08-30.
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