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 tomzx/agents --skill identify-feature-opportunitiesgit clone --depth 1 https://github.com/tomzx/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/tomzx/agents/identify-feature-opportunities)<a href="https://agentmods.dev/skills/tomzx/agents/identify-feature-opportunities"><img src="https://agentmods.dev/badge/skills/tomzx/agents/identify-feature-opportunities.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00127 | $0.04056 |
| Opus 5 | $0.00063 | $0.02028 |
| Sonnet 5 | $0.00025 | $0.00811 |
| Haiku 4.5 | $0.00013 | $0.00406 |
Grade A, and why
identify-feature-opportunities scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TODAY=!date +%Y-%m-%d
REPO=!git remote get-url origin 2>/dev/null | sed -E 's#.*[:/]([^/]+/[^/]+)(\.git)?$#\1#'
Identify Feature Opportunities
Surfaces new feature opportunities by reading the software as it actually exists today and the signals around it, then synthesizing concrete, evidenced ideas ranked by value and strategic fit. This is discovery: it proposes work that does not yet exist, unlike prioritize-issues (ranks existing issues), check-issues-status (finds done work), or create-needs-assessment (validates one proposed idea).
The Core Problem This Solves
Roadmaps and backlogs fill up from incoming requests, but they rarely get a bottom-up re-derivation from the software itself. Capabilities get 80% built and abandoned, adjacent expansion paths go unnoticed, repeated issue themes never get generalized into a feature, and stated goals sit with no corresponding code. This skill reads the codebase as evidence of what exists and proposes what is missing.
Prerequisites
- Working directory is the root of a
gitrepository ghCLI authenticated with read access to the target repository (for issue and PR signals)- Read any files under
.sdlc/context/(project-overview.md,goals.md,roadmap.md,architecture.md) for strategic context. These are optional but materially improve alignment scoring. - If no argument is provided, operate on
$REPO(derived fromorigin), then the current working directory.
Inputs Synthesized
The skill reasons over five evidence sources. Each opportunity must cite at least one; strong opportunities cite two or more.
| Source | What it reveals |
|---|---|
| Code surface | CLI commands, API endpoints, UI screens, modules, config keys. What exists, what is stubbed, what is asymmetrically mature. |
.sdlc/context/ |
Stated goals, roadmap initiatives, positioning. Used to score alignment and to find goals with no backing code. |
| Open + recent issues | User pain and requests. Clusters of same-theme issues signal unmet need, not random bugs. |
| Merged PR history | Recent themes and velocity. Momentum in one area hints at adjacent expansion. |
| README / docs | Stated capabilities vs. actual. Positioning reveals the product category and its expected feature set. |
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.
- 5d ago First seen · 289 lines · 127 tokens per session scan A f7563ae3a779
identify-feature-opportunities is a skill published in the GitHub repository tomzx/agents (6 stars, last pushed 4d ago), licensed MIT. It adds 127 tokens to every session and 4,056 once invoked, about $0.0006 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.
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