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 VandanaAjayDubey111/great-pm --skill obviously-awesomegit clone --depth 1 https://github.com/VandanaAjayDubey111/great-pmWrote 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/vandanaajaydubey111/great-pm/obviously-awesome)<a href="https://agentmods.dev/skills/vandanaajaydubey111/great-pm/obviously-awesome"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/obviously-awesome/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/vandanaajaydubey111/great-pm/obviously-awesome"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/obviously-awesome.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 | $0.00122 | $0.05145 |
| Opus 5.5 | $0.00049 | $0.02058 |
| Sonnet 5.5 | $0.00024 | $0.01029 |
| Haiku 4.5 | $0.00012 | $0.00515 |
Grade A, and why
obviously-awesome 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 1mo 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.
This is a copy
89% identical to neversight_learn_skills.dev_obviously_awesome — 18 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 — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex host binding
- Treat references to Claude slash workflows as the equivalently named Codex skill.
- Before delegating to any specialist, read the
great-pm-runtimeskill and the selected packaged role file. - Treat "invoke", "assign", "delegate", "spawn", and source Agent-tool instructions as a required Codex
spawn_agentcall with that role and a bounded assignment. - For the spawn tool's
task_nameoragent_nameidentifier, replace canonical role-name hyphens with underscores (query-refiner-pm→query_refiner_pm). Keep canonical names unchanged in prompts, filenames, verdict logs, and user-facing output; this is an internal identifier mapping, not a role rename. - Store every returned agent identifier. Never call a wait tool until a spawn has returned an identifier, and wait only on identifiers returned by successful spawns.
- If
spawn_agentis unavailable or a spawn fails, report BLOCKED; do not impersonate the specialist or wait on an empty agent set. - Resolve bundled paths from the installed GreatPM plugin root.
- Ignore Claude-only model aliases, colors, turn limits, and tool allowlists.
- Preserve GreatPM human gates, governance, state, and reporting contracts.
Provenance. Vendored from
wondelai/skills@obviously-awesome(MIT License — github.com/wondelai/skills). Adapted into great-pm 2026-05-29 with attribution. Reference deep-dives (references/*.md) live upstream. Host agent: gtm-strategist.
Product Positioning Framework
This skill implements the product positioning methodology from April Dunford's "Obviously Awesome." It provides a structured, repeatable process for defining how your product is the best in the world at delivering something a well-defined set of customers cares a lot about. Positioning is the foundational strategic exercise that determines how customers perceive your product, what they compare it to, and ultimately whether they buy it.
Core Principle
Positioning is not messaging. Positioning is context.
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.
- 1mo ago First seen · 316 lines · 122 tokens per session scan A bbe5bf7e37cb
obviously-awesome is a skill published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 122 tokens to every session and 5,145 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to neversight_learn_skills.dev_obviously_awesome, differing in 18 lines, and is treated as a copy.
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