> ## Documentation Index
> Fetch the complete documentation index at: https://docs.synscribe.com/llms.txt
> Use this file to discover all available pages before exploring further.

# How to check if you can rank for a keyword

> Quality-gate a batch of candidate keywords with keyword-evaluation and serp-cliff-analysis, the ACCEPT / REVIEW / REJECT "can I win?" gate.

Ask Pi to run the batch through `keyword-evaluation` (a 5-dimension ACCEPT / REVIEW / REJECT gate) and
`serp-cliff-analysis`, which reads the live SERP to find the cliff — the position where result quality
drops off. A low cliff (weak pages ranking by accident) is your insertion point; a high cliff (strong,
exact-match, high-authority top results) means you're locked out. Both skills are read-only, so they
report without changing keyword state; you tag the ACCEPTs next in
[2.2.3](/platform/organise-tag-file-keywords). This is why you pick keywords on the cliff, not on
volume.

> **Pick keywords on the SERP cliff, not on volume.** Drop keywords you can't win, even
> high-volume ones. See [Part 1 §1.4 SERP cliff](/theory/serp-cliff), and the
> one-intent / no-self-competition rule in [§1.5 Intent & cannibalization](/theory/intent-cannibalization).

`keyword-evaluation` grades each keyword against five dimensions (2-D label fit, SERP cliff, intent
winnability, ICP/offering specificity, and evidence/source) and it never relies on keyword
difficulty. Every non-ACCEPT verdict comes with an Exploration Prescription: a named tactic and the
literal next tool call to run, not vague feedback. It also surfaces weak-competitor openings as
"leads worth chasing." The skill is read-only, so it reports without mutating keyword state; tagging
and filing happen afterward in [2.2.3](/platform/organise-tag-file-keywords).

## How the verdicts map to action

| Verdict    | What it means                                                                      | What you do                                              |
| ---------- | ---------------------------------------------------------------------------------- | -------------------------------------------------------- |
| **ACCEPT** | Winnable, relevant, right intent                                                   | Keep, then tag it into the cycle                         |
| **REVIEW** | Promising but flagged: soft SERP unclear, borderline intent, or needs human triage | Read the Exploration Prescription, then refine or decide |
| **REJECT** | Locked-out SERP, wrong intent, no demand, or a content-idea query                  | Drop, or reshape per the prescription                    |

The SERP-cliff read layers on top. A low cliff (weak pages ranking by accident, no exact-title
match, low domain authority) is your insertion point. A high cliff (positions 1-7 all strong,
exact-match, high-authority) means you're locked out, so defer or find a softer variant.

## Steps

1. Select the candidate batch in the Keywords dashboard (from [2.2.1](/platform/keyword-exploration)).
2. Ask Pi to run it through the keyword evals + SERP cliff.
3. Read the report: ACCEPT / REVIEW / REJECT per keyword, plus cliff position and "are you already
   ranking?" for each.
4. Apply the verdict rubric below, including the drop/keep/optimize decision when you already
   rank.
5. Hand the ACCEPTs to tagging in [2.2.3](/platform/organise-tag-file-keywords).

## Real prompts

The blunt version. Run everything through the gate:

```text theme={null}
look at ALL the keywords right now and run it through the keyword evals.
```

Pi runs `keyword-evaluation` and returns a per-keyword ACCEPT / REVIEW / REJECT report with an
Exploration Prescription on every non-ACCEPT and "leads worth chasing" where a competitor is winning
without deserving it.

The full winnability + cannibalization pass with SERP cliff:

```text theme={null}
use the keyword explorer and serp cliff to check through all the drafted keywords. for each:
- get US volume
- run serp cliff analysis
- check if it already has a landing page (no duplicates / cannibalization)
- check if we already rank for it and at what position
- flag any keywords in our list too similar to each other (pick the stronger, drop the other)
```

The keep/drop/optimize rubric when you may already rank (paste positions back in):

```text theme={null}
before we commit these, check the SERP for each and whether [my company] already ranks:
- already #1/#2 → drop (don't build a competing page)
- not ranked yet → keep
- striking distance (pos 8–20, high impressions) → keep to optimize the existing page
```

> 🎬 **Video planned:** select a batch, run evaluation, read the SERP-cliff signal, make the
> keep/cut decision. See the shot-list.

***

**Previous:** [2.2.1 Keyword exploration](/platform/keyword-exploration) · **Next:** [2.2.3 Organise, tag & file keywords](/platform/organise-tag-file-keywords) · **Theory:** [Part 1 §1.4 SERP cliff](/theory/serp-cliff) · [§1.5 Intent & cannibalization](/theory/intent-cannibalization) · **The rigorous cycle version:** [3.4 Organise keywords for a cycle](/sops/organise-keywords)