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 sananthanarayan/skilldrop --skill success-metricsgit clone --depth 1 https://github.com/sananthanarayan/skilldropWrote 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/sananthanarayan/skilldrop/success-metrics)<a href="https://agentmods.dev/skills/sananthanarayan/skilldrop/success-metrics"><img src="https://agentmods.dev/badge/skills/sananthanarayan/skilldrop/success-metrics/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/sananthanarayan/skilldrop/success-metrics"><img src="https://agentmods.dev/badge/skills/sananthanarayan/skilldrop/success-metrics.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 | $0.00093 | $0.01607 |
| Opus 5 | $0.00046 | $0.00804 |
| Sonnet 5 | $0.00019 | $0.00321 |
| Haiku 4.5 | $0.00009 | $0.00161 |
Grade A, and why
success-metrics 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 9d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
success-metrics
Answers "how will we know it worked?" before build, when the answer can still change what gets built — and makes the measurement honest by pre-committing the decision rule, naming the counter-metric that catches gaming, and writing the instrumentation plan so launch day isn't the day someone discovers no event fires. Expands the one-line success criteria in a prd-draft into the full measurement design.
How to respond
-
Extract the goal from the PRD, brief, or conversation. Ask at most 2 questions, spent on baseline ("what's the number today, and where does it live?") and decision authority ("who acts if the target is missed?"). No goal articulated yet → stop and route to
prd-draft; metrics for an unstated goal measure noise. Non-interactive run (no user to ask): a stated-but-vague goal gets sharpened and tagged[assumption]; no goal at all → emitBLOCKED: need the feature's goal— never invent one. -
Pick exactly one primary metric. More than one primary means none — when they diverge, nobody pre-agreed which wins. The primary is an outcome the user experiences or the business banks, not an output the team ships. ✅ "Median support-ticket handle time" — ❌ "Number of dashboard features launched" — ❌ "Dashboard page views" (attention is not outcome). Every other contender becomes a secondary, guardrail, or gets cut.
-
Give the primary its three numbers: baseline (today's value + source; if unknown, the first milestone of the plan is measuring it — a target without a baseline is a guess about a guess), target (the value that means "worked"), timeframe (when judged, plus the patience window — how long after launch before the data is trusted: novelty effects, weekly cycles, cohort maturity).
-
Add leading indicators — 2–3 metrics that move within days and plausibly predict the primary, each with its causal sentence: ✅ "% of tickets where the agent opens the unified view — if agents don't adopt it, handle time can't drop". Leading indicators are for steering mid-flight; only the primary decides success.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 64 lines · 93 tokens per session scan A d949f0c30873
success-metrics is a skill published in the GitHub repository sananthanarayan/skilldrop (2 stars, last pushed 26d ago), licensed MIT. It adds 93 tokens to every session and 1,607 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
readme
This skill should be used to audit OR elevate the README of a public repository. Trigger with "improve the README", "make the readme high quality", "elevate this readme", "audit the readme", "add badges", "is our README good", or before publishing/releasing a repo. Elevate rebuilds a thin/generic README to a polished…
cairn-attention
Resolve Cairn's pending-attention queue inline (DEC drafts, baseline findings, drift events).
cairn-direction
Spec-tightener + subagent dispatcher. Engage on code-change asks — verbs, bug reports, observations. Pivot-aware on active tasks.
cairn-resync
Operator-initiated re-discovery — resolve config drift, re-cluster topics, re-curate grown areas into DEC/INV drafts.
ship
Execute an approved pitch/spec as a delegated, closed-scope cycle with verification and adversarial review. Invoke it yourself with /ship — a cycle spawns a writer and opens a PR, so it starts when you say so. Enforces the execution playbook: right-size gate, pre-spawn filter, doc-bundle, PR format, review.
adr-new
Create a new Architecture Decision Record with append-only, status-gated supersession, and update the ADR index. Invoke with /adr-new, or let /tdd-author invoke it on approval of an ADR action (this skill stays model-invocable for that reason).