Coral is a local application that gives AI agents one SQL interface for querying connected APIs, files, and live data sources. It is for agents and developers who need to retrieve and correlate data across sources while reducing repeated tool calls, pagination, and source-specific integration code. Coral exposes its query interface to compatible agents through MCP, and the catalogue add-ons support using it in agent workflows.
Borrowing it
Nothing to install: this file belongs to withcoral/coral. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/withcoral/coral/main/.agents/skills/implement-spec/SKILL.mdgit clone --depth 1 https://github.com/withcoral/coralWrote 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/withcoral/coral/implement-spec)<a href="https://agentmods.dev/skills/withcoral/coral/implement-spec"><img src="https://agentmods.dev/badge/skills/withcoral/coral/implement-spec/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/withcoral/coral/implement-spec"><img src="https://agentmods.dev/badge/skills/withcoral/coral/implement-spec.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 | $0.00018 | $0.00591 |
| Opus 5.5 | $0.00007 | $0.00236 |
| Sonnet 5.5 | $0.00004 | $0.00118 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
implement-spec 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 3d 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- implement-spec — 100% identical, 0 lines differ
- implement-spec — 100% identical, 0 lines differ
- implement-spec — 100% identical, 0 lines differ
- implement-spec — 100% identical, 0 lines differ
What it actually says
You have been provided a spec. This spec should have tickets associated with it, describing how to implement the spec.
The issue tracker should have been provided to you. If not, tell the user to run /setup-matt-pocock-skills.
The goal is the entire spec implemented on a single integration branch, with every ticket resolved the way the issue tracker closes work.
The tickets are not a list of steps. They are a task graph with blocking relationships between them. This means there is always a frontier of tickets which are ready to be grabbed.
Communication to and from subagents should be sparse. Communicate primarily through context pointers: to the spec, tickets, research notes, and previous commits. Don't duplicate information already available via pointers.
Implementer subagents should be run in the background where possible for maximum concurrency.
Steps
-
Read the spec and tickets to understand the task graph.
-
(optional) Use an exploration subagent to conduct any exploration required by the tickets - relevant codebase files or external documentation. Ensure the exploration subagent can save files - it should save its markdown notes in a directory outside the repo, accessible by all future subagents. This lets implementer subagents focus on implementation rather than exploration.
-
Create the integration branch. If the issue tracker closes work through PRs, or the user asks for one, open a draft PR after the first merge in step 5 (a branch with no commits ahead of main can't open one), marked as closing the spec and tickets.
-
Use implementer subagents to implement each ticket, each in its own worktree on its own branch. Each implementer subagent:
- confirms its worktree is based on the integration branch before starting, and resets onto it if not;
- calls the Skill tool with
tddto build the ticket; - merges the integration branch tip into its own branch before reporting done
-
Once an implementer subagent completes, merge its work to the integration branch with a merger subagent.
-
If this changes the frontier of available tickets, kick off more implementer subagents to work on the new tickets. This allows for maximum concurrency.
-
Once all tickets are complete, call the Skill tool with
code-reviewon the integration branch. Fix all issues raised by the code review in a single implementer subagent. -
If a draft PR exists, mark it ready for review. Otherwise, resolve each ticket the way the issue tracker closes work, and report the integration branch.
-
Clean up all implementer subagent worktrees.
What ships with it
1 file 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.
- 3d ago First seen · 41 lines · 18 tokens per session scan A 7a22dd2e60b8
implement-spec is a skill published in the GitHub repository withcoral/coral (4,936 stars, last pushed today), licensed Apache-2.0. It adds 18 tokens to every session and 591 once invoked, about $0.0001 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 2026-10-13.
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